3,212 results on '"fuzzy cognitive map"'
Search Results
202. Design Method of FCM Representation with Optimization Algorithm
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Yuan, Haibin, Wu, QiCai, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Zhang, Lin, editor, Song, Xiao, editor, and Wu, Yunjie, editor
- Published
- 2016
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203. Network Neutrality in the IoT: A Fuzzy Cognitive Map Extend Technology Roadmap Perspective
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Xing, Bo, Sammes, A.J., Series editor, and Mahmood, Zaigham, editor
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- 2016
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204. Verbalization of Dependencies Between Concepts Built Through Fuzzy Cognitive Maps
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Wehrle, Marcel, Osswald, Marc, Portmann, Edy, Kacprzyk, Janusz, Series editor, Portmann, Edy, editor, and Finger, Matthias, editor
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- 2016
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205. Evaluation of supply chain configuration criteria using fuzzy cognitive map.
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Dursun, Mehtap, Goker, Nazli, and Gumus, Guray
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SUPPLY chains , *SUPPLY chain management , *TECHNICAL specifications - Abstract
This study proposes a comprehensive configuration for supply chain management process and it enables to understand relationships among supply chain integration, supply chain strategies, supply chain risk factors, and performance criteria. Supply chain configuration criteria are determined both reviewing the literature and using experts’ knowledge and fuzzy cognitive map methodology is employed to consider the interrelations between criteria. Fuzzy cognitive map methodology is a suitable tool due to the presence of causalities, positive as well as negative directions of relationships among criteria, and the difficulty of expressing the interrelations with crisp numbers. The application is conducted in an automobile manufacturer in Turkey, and the results are analyzed. [ABSTRACT FROM AUTHOR]
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- 2019
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206. VALIDACIÓN DE CAPAS CONVOLUCIONALES EN MODELOS DEEP LEARNING PARA LA IDENTIFICACIÓN DE PATRONES EN IMÁGENES MULTIESPECTRALES: Identificación de unidades de cultivo de palma.
- Author
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Peña, Alejandro, Bonet, Isis, Manzur, Diego, Góngora, Mario, and Caraffini, Fabio
- Abstract
Copyright of CISTI (Iberian Conference on Information Systems & Technologies / Conferência Ibérica de Sistemas e Tecnologias de Informação) Proceedings is the property of Conferencia Iberica de Sistemas Tecnologia de Informacao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2019
207. Prioritizing Construction Labor Productivity Improvement Strategies Using Fuzzy Multi-Criteria Decision Making and Fuzzy Cognitive Maps
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Matin Kazerooni, Phuong Nguyen, and Aminah Robinson Fayek
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construction labor productivity ,fuzzy multi-criteria decision making ,fuzzy cognitive map ,productivity improvement strategy ,impact quantification ,Industrial engineering. Management engineering ,T55.4-60.8 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Construction labor productivity (CLP) is affected by various interconnected factors, such as crew motivation and working conditions. Improved CLP can benefit a construction project in many ways, such as a shortened project life cycle and lowering project cost. However, budget, time, and resource restrictions force companies to select and implement only a limited number of CLP improvement strategies. Therefore, a research gap exists regarding methods for supporting the selection of CLP improvement strategies for a given project by quantifying the impact of strategies on CLP with respect to interrelationships among CLP factors. This paper proposes a decision support model that integrates fuzzy multi-criteria decision making with fuzzy cognitive maps to prioritize CLP improvement strategies based on their impact on CLP, causal relationships among CLP factors, and project characteristics. The proposed model was applied to determine CLP improvement strategies for concrete-pouring activities in building projects as an illustrative example. This study contributes to the body of knowledge by providing a systematic approach for selecting appropriate CLP improvement strategies based on interrelationships among the factors affecting CLP and the impact of such strategies on CLP. The results are expected to support construction practitioners with identifying effective improvement strategies to enhance CLP in their projects.
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- 2021
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208. A Report on Studies in Private Engineering Colleges Using Fuzzy Cognitive Map (FCM)
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Mukthar, M. Mohamed Salih
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- 2017
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209. Modelling Differential Diagnosis of Febrile Diseases with Fuzzy Cognitive Map
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Uzoka, Okure Obot, Anietie John, Iberedem Udo, Kingsley Attai, Ekemini Johnson, Samuel Udoh, Chukwudi Nwokoro, Christie Akwaowo, Emem Dan, Uduak Umoh, and Faith-Michael
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fuzzy cognitive map ,febrile diseases ,malaria ,enteric fever ,laser fever ,yellow fever ,dengue fever ,HIV/AIDS ,tuberculosis ,urinary-tract infection ,respiratory-tract infection - Abstract
The report of the World Health Organization (WHO) about the poor accessibility of people living in low-to-middle-income countries to medical facilities and personnel has been a concern to both professionals and nonprofessionals in healthcare. This poor accessibility has led to high morbidity and mortality rates in tropical regions, especially when such a disease presents itself with confusable symptoms that are not easily differentiable by inexperienced doctors, such as those found in febrile diseases. This prompted the development of the fuzzy cognitive map (FCM) model to serve as a decision-support tool for medical health workers in the diagnosis of febrile diseases. With 2465 datasets gathered from four states in the febrile diseases-prone regions in Nigeria with the aid of 60 medical doctors, 10 of those doctors helped in weighting and fuzzifying the symptoms, which were used to generate the FCM model. Results obtained from computations to predict diagnosis results for the 2465 patients, and those diagnosed by the physicians on the field, showed an average of 87% accuracy for the 11 febrile diseases used in the study. The number of comorbidities of diseases with varying degrees of severity for most patients in the study also covary strongly with those found by the physicians in the field.
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- 2023
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210. Fuzzy Cognitive Maps and Multi-step Gradient Methods for Prediction: Applications to Electricity Consumption and Stock Exchange Returns
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Papageorgiou, Elpiniki I., Poczęta, Katarzyna, Yastrebov, Alexander, Laspidou, Chrysi, Howlett, Robert J., Series editor, Jain, Lakhmi C., Series editor, and Neves-Silva, Rui, editor
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- 2015
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211. Modelling Knowledge Management Processes Using Fuzzy Cognitive Maps
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Prochazka, Ondrej, Hajek, Petr, van der Aalst, Wil, Series editor, Mylopoulos, John, Series editor, Rosemann, Michael, Series editor, Shaw, Michael J., Series editor, Szyperski, Clemens, Series editor, Uden, Lorna, editor, Heričko, Marjan, editor, and Ting, I-Hsien, editor
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- 2015
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212. Analyzing Dynamic Capabilities via Fuzzy Cognitive Maps
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Çoban, Veysel, Çevik Onar, Sezi, Soyer, Ayberk, Kacprzyk, Janusz, Series editor, Jain, Lakhmi C., Series editor, Kahraman, Cengiz, editor, and Çevik Onar, Sezi, editor
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- 2015
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213. Timed Fuzzy Cognitive Maps for Supporting Obstetricians’ Decisions
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Bourgani, Evangelia, Stylios, Chrysostomos D., Manis, George, Georgopoulos, Voula C., MAGJAREVIC, Ratko, Editor-in-chief, Ładyzynsk, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, and Vasic, Darko, editor
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- 2015
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214. Expert-Based Method of Integrated Waste Management Systems for Developing Fuzzy Cognitive Map
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Buruzs, Adrienn, Hatwágner, Miklós F., Kóczy, László T., Kacprzyk, Janusz, Series editor, Zhu, Quanmin, editor, and Azar, Ahmad Taher, editor
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- 2015
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215. Monitoring and Prediction of Time Series Based on Fuzzy Cognitive Maps with Multi-step Gradient Methods
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Poczęta, Katarzyna, Yastrebov, Alexander, Kacprzyk, Janusz, Series editor, Szewczyk, Roman, editor, Zieliński, Cezary, editor, and Kaliczyńska, Małgorzata, editor
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- 2015
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216. Integrated Approach for Developing Timed Fuzzy Cognitive Maps
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Bourgani, Evangelia, Stylios, Chrysostomos D., Manis, George, Georgopoulos, Voula C., Kacprzyk, Janusz, Series editor, Angelov, P., editor, Atanassov, K.T., editor, Doukovska, L., editor, Hadjiski, M., editor, Jotsov, V., editor, Kacprzyk, J., editor, Kasabov, N., editor, Sotirov, S., editor, Szmidt, E., editor, and Zadrożny, S., editor
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- 2015
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217. A Multi-Level Linguistic Fuzzy Decision Network Hierarchical Structure Model for Crop Selection
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Elomda, Basem Mohamed, Hefny, Hesham Ahmed, Ashmawy, Fathy, Hazman, Maryam, Hassan, Hesham Ahmed, Kacprzyk, Janusz, Series editor, Filev, D., editor, Jabłkowski, J., editor, Kacprzyk, J., editor, Krawczak, M., editor, Popchev, I., editor, Rutkowski, L., editor, Sgurev, V., editor, Sotirova, E., editor, Szynkarczyk, P., editor, and Zadrozny, S., editor
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- 2015
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218. A Brief Survey on Fuzzy Cognitive Maps Research
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Wang, Yajie, Zhang, Weiyuan, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Huang, De-Shuang, editor, and Han, Kyungsook, editor
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- 2015
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219. Dynamics of Fuzzy-Rough Cognitive Networks
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István Á. Harmati
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fuzzy-rough cognitive network ,fuzzy cognitive map ,granular computing ,fuzzy-rough sets ,stability ,convergence ,Mathematics ,QA1-939 - Abstract
Fuzzy-rough cognitive networks (FRCNs) are interpretable recurrent neural networks, primarily designed for solving classification problems. Their structure is simple and transparent, while the performance is comparable to the well-known black-box classifiers. Although there are many applications on fuzzy cognitive maps and recently for FRCNS, only a very limited number of studies discuss the theoretical issues of these models. In this paper, we examine the behaviour of FRCNs viewing them as discrete dynamical systems. It will be shown that their mathematical properties highly depend on the size of the network, i.e., there are structural differences between the long-term behaviour of FRCN models of different size, which may influence the performance of these modelling tools.
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- 2021
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220. A hybrid method using fuzzy cognitive map- DEA to study the delays in construction projects
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Samuel Yousefi, Serveh Kakaei, and Mustafa Jahangoshai Rezaee
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delay ,construction projects ,fuzzy cognitive map ,fuzzy dea. 1 ,Industrial engineering. Management engineering ,T55.4-60.8 - Abstract
Delay is a common occurrence in the country's construction projects. Identifying delay factors in these projects and determining the influence of these factors is necessary to achieve the objectives of management. In this study, the effective delay factors on construction projects are identified by using previous studies, project documents and experts opinions. Since these factors affect on each other, the fuzzy cognitive map has drawn for effective factors and assessment factors or management objectives. Then, the effect of each factor on the assessment factors are evaluated by using hybrid learning algorithm and prioritization factors are done by using fuzzy data envelopment analysis. The results of the survey in West Azerbaijan province show that “supervision technical weaknesses for overcoming technical and executive workshop problems”, “inaccurate estimate of workload, required equipments and project time” and “the multiplicity of decision centers on the doing of projects” are the most important delay factors in construction projects
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- 2017
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221. Когнитивная модель для исследования уровня защищенности объекта критической инфра-структуры
- Subjects
інформаційна безпека ,security threats ,information security ,критична інфраструктура ,нечеткая когнитивная карта ,информационная безопасность ,критическая инфраструктура ,угрозы безопасности ,fuzzy cognitive map ,cognitive modeling ,когнитивное модели-рование ,когнітивне моделювання ,УДК 004.056.53 ,UDC 004.056.53 ,critical infrastructure ,нечітка когні-тивна карта ,загрози безпеці - Abstract
The protection of critical infrastructure is strategically important for the functioning of the economy and security of the state, society and the population. To address the protection of critical infrastructure, it is necessary to analyze potential threats, explore the relationships between them and determine the impact of these threats on the system under study. However, there are some difficulties associated with a high degree of uncertainty, the complexity of strict formalization and the subjective nature of these tasks. In this regard, the paper proposes the use of a cognitive approach, which does not require a large amount of experimental data, provides an opportunity to process the information available to the expert and take into account both qualitative and quantitative factors. Based on this approach, a cognitive model was created, which is based on a fuzzy cognitive map and allows to study the impact of potential threats on the level of protection of critical infrastructure. To build a fuzzy cognitive map, many of the most important critical infrastructure threats from the point of view of this problem have been formed and causal links have been established between them. The evaluation of structural and topological properties of fuzzy cognitive map is carried out, its density, hierarchy index and centrality of concepts are determined. From the set of expertly formed set of concepts, the most important ones are selected. To determine the relative change in the level of protection of the critical infrastructure, a scenario modeling of the impact of the most important concepts on the studied system was performed. Based on the analysis of the data obtained as a result of the launch of appropriate scenarios, it is possible to prevent disruption of key elements of critical infrastructure, which, in turn, can lead to emergencies that can paralyze the lives of individual cities and the state as a whole. Для решения вопросов по обеспечению защищенности объектов критической инфраструктуры необходимо проанализировать потенциальные угрозы, исследовать взаимосвязи между ними и определить влияние данных угроз на исследуемую систему. При этом появляются некоторые трудности связаны с высокой степенью неопределенности, сложности строгой формализации и субъективным характером данных задач. В связи с этим в работе предлагается использование когнитивного подхода, который не требует большого объема экспериментальных данных, дает возможность обрабатывать доступную экспертную информацию и учитывать, как качественные, так и количественные факторы. На основе данного подхода была создана когнитивная модель, которая основанная на нечеткой когнитивной карте и позволяет проанализировать влияние потенциальных угроз на уровень защищенности объектов критической инфраструктуры. Осуществлено оценивания структурно-топологических свойств нечеткой когнитивной карты, определены ее плотность, индекс иерархии и центральность концептов. С множества концептов выделены наиболее весомые. Проведено сценарное моделирование влияния данных концептов на защищенность объектов критической инфраструктуры. Данные получены в результате запуска соответствующих сценариев позволяют исследовать относительное изменение исследуемой системы и способствуют эффективному решению вопросов по повышению уровня защищенности объектов критической инфраструктуры. Для вирішення питань щодо забезпечення захищеності об’єктів критичної інфраструктури необхідно проаналізувати потенційні загрози, дослідити взаємозв’язки між ними та визначити вплив даних загроз на досліджувану систему. При цьому з’являються деякі труднощі пов’язані із високим ступенем невизначеності, складністю строгої формалізації та суб’єктивним характером даних задач. У зв’язку з цим у роботі пропонується використання когнітивного підходу, який не потребує великого обсягу експериментальних даних, надає можливість опрацьовувати доступну експерту інформацію та враховувати як якісні так і кількісні фактори. На основі даного підходу було створено когнітивну модель, яка базуються на нечіткій когнітивній карті та дозволяє дослідити вплив потенційних загроз на рівень захищеності об’єкта критичної інфраструктури. Здійснено оцінювання структурно-топологічних властивостей нечіткої когнітивної карти, визначено її щільність, індекс ієрархії та центральність концептів. Із сформованої експертним шляхом множини концептів виділено найбільш вагомі. Проведено сценарне моделювання впливу даних концептів на захищеність об’єкта критичної інфраструктури. Дані отримані у результаті запуску відповідних сценаріїв дозволяють дослідити відносну зміну досліджуваної системи та сприяють ефективному вирішенню питань щодо підвищення рівня захищеності об’єктів критичної інфраструктури.
- Published
- 2023
222. The Modeling of Time Series Based on Least Square Fuzzy Cognitive Map
- Author
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Guoliang Feng, Wei Lu, and Jianhua Yang
- Subjects
time series ,least square method ,fuzzy cognitive map ,refinements of concepts ,Industrial engineering. Management engineering ,T55.4-60.8 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
A novel design method for time series modeling and prediction with fuzzy cognitive maps (FCM) is proposed in this paper. The developed model exploits the least square method to learn the weight matrix of FCM derived from the given historical data of time series. A fuzzy c-means clustering algorithm is used to construct the concepts of the FCM. Compared with the traditional FCM, the least square fuzzy cognitive map (LSFCM) is a direct solution procedure without iterative calculations. LSFCM model is a straightforward, robust and rapid learning method, owing to its reliable and efficient. In addition, the structure of the LSFCM can be further optimized with refinements the position of the concepts for the higher prediction precision, in which the evolutionary optimization algorithm is used to find the optimal concepts. Withal, we discussed in detail the number of concepts and the parameters of activation function on the impact of FCM models. The publicly available time series data sets with different statistical characteristics coming from different areas are applied to evaluate the proposed modeling approach. The obtained results clearly show the effectiveness of the approach.
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- 2021
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223. A Fuzzy Cognitive Map Approach for Performance Indicators Evaluation of Suppliers in Turkish Textile Industry.
- Author
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Dursun, Mehtap, Goker, Nazli, and Kolak, Orhan Ilker
- Subjects
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COGNITIVE maps (Psychology) , *PERFORMANCE evaluation , *SUPPLIERS , *TEXTILE industry , *PERFORMANCE management - Abstract
This study proposes a multi-criteria decision approach, called as fuzzy cognitive map (FCM), which represents experts' knowledge and human experience, and aims to evaluate performance indicators of suppliers in the textile industry by introducing concepts to define criteria and causality links among the concepts for modeling a system's behavior. The contribution of the study will be the fact that any other researcher has not been incorporated the FCM methodology into the supplier performance evaluation. [ABSTRACT FROM AUTHOR]
- Published
- 2018
224. Development and implementation of product sustainment simulator utilizing fuzzy cognitive map (FCM)
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Benedict M. Uzochukwu, Silvanus J. Udoka, and Femi Balogun
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- 2016
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225. Multi-level Linguistic Fuzzy Decision Network Hierarchical Structure Model for MCDM
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Elomda, Basem Mohamed, Hefny, Hesham Ahmed, Hazman, Maryam, Hassan, Hesham Ahmed, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Tanaka, Yuzuru, editor, Wahlster, Wolfgang, editor, Siekmann, Jörg, editor, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, and Wang, Ling, editor
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- 2014
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226. Time Dependent Fuzzy Cognitive Maps for Medical Diagnosis
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Bourgani, Evangelia, Stylios, Chrysostomos D., Manis, George, Georgopoulos, Voula C., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Tanaka, Yuzuru, editor, Wahlster, Wolfgang, editor, Siekmann, Jörg, editor, Likas, Aristidis, editor, Blekas, Konstantinos, editor, and Kalles, Dimitris, editor
- Published
- 2014
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227. Analysis of influencing factors in emergency management based on an integrated methodology.
- Author
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Liu, Xiaodi, Wang, Zengwen, Zhang, Shitao, and Liu, Jiashu
- Subjects
- *
EMERGENCY management , *PEARSON correlation (Statistics) , *FACTOR analysis - Abstract
Various emergencies are happening frequently in recent years, causing great loss of life and property. Therefore, it has become imperative to improve emergency management. Considering that the performance of emergency management could be affected by many different factors, it is hard to improve all the factors under the condition of limited resources. One approach that works well is to optimize the key factors that affect emergency management. To this end, an integrated method based on fuzzy cognitive map (FCM) and Pearson's product-moment correlation coefficient is presented in this article to determine the critical risk factors in emergency management. First, the causal relationships between the risk factors influencing emergency management are determined according to expert opinions. To verify if the survey results from experts are reliable, an item-average correlation test based on Pearson's product-moment correlation coefficient is performed. Then, two scenarios are designed and the FCM method is utilized to identifying the critical risk factors of emergency management. Finally, five critical factors are figured out, and the efficiency of emergency management could be enhanced by optimizing these five factors. In addition, a comparative analysis is also conducted to validate the advantages of the proposed method. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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228. Critical barriers to the introduction of shore power supply for green port development: case of Djibouti container terminals.
- Author
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Radwan, Mohamed Elmi, Chen, Jihong, Wan, Zheng, Zheng, Tianxiao, Hua, Chengying, and Huang, Xiaoling
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CONTAINER terminals ,SUSTAINABLE development ,POWER resources ,PORT districts ,EMISSIONS (Air pollution) ,AIR quality - Abstract
Greenhouse gas emissions and air pollutants from ships contribute to climate change and poor local air quality. While at berth, the use of shore-side electricity as an alternative technique to generate electricity to ships can greatly reduce emissions and improve air quality. The container terminals of Djibouti accommodate a significant number of ship calls, but there is a lack of emissions mitigation measures. The purpose of this study is to identify the most critical barriers that hinder the deployment of shore power supply in the container terminals of Djibouti. To achieve this aim, this study consults professional experts and experienced managers working in the maritime industry. The data collection is based on a survey questionnaire collected in the form of linguistic preferences to handle fuzziness of human perceptions. The collected linguistic preferences are later converted into quantitative data and analyzed using fuzzy cognitive map approach. The results reveal that power requirement, investment cost and electricity cost are the key barriers that currently influence the implementation of the shore power technology in Djibouti. The findings of the study have great implications and are hoped to assist decision makers and port authority in prioritizing the different barriers according to their importance, in an effort to accelerate the introduction and the development of green port strategies. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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229. Cognitive mapping concept of the resource management for the viability of local communities.
- Author
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Trostianska, K., Semencha, I., and Yerina, M.
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CONCEPT mapping ,RESOURCE management ,BUILDING operation management ,CONSTRUCTION management ,COMMUNITIES - Abstract
The local community is a complex socio-economic system, and its ability to function for an indefinitely long period of time (viability) is not investigated sufficiently today. The purpose of the research was, using the cognitive mapping, propose to the local community management developing their own management strategies to ensure its viability. Considering the weakly structured subject area of resource management for the viability of the local community and the complex dynamic nature of socio-economic processes, fuzzy cognitive reflection was suggested as a tool that provides opportunities for modeling the inherent complexity and uncertainty associated with socio-economic systems. This research shows a system of relations between concepts in the form of a causative network – a cognitive map of the resource management of a local community and proposes scales for measuring the concepts. During the simulation experiments, managed, indirectly managed and unmanaged resources for the viability of a local community were defined. In modeling, own income per inhabitant has been chosen as the target concept and as an indicator of the potential of an independent choice of direction for the development of the local community with the view toward the construction of resource management scenarios for the local community’s viability. As a result of the simulation, there were proposed some strategies for the growth of ‘own income per inhabitant’ and some recommendations were given for building management scenarios within these strategies. [ABSTRACT FROM AUTHOR]
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- 2019
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230. Causal reasoning of emergency cases based on Fuzzy Cognitive Map.
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Qiu, Jiangnan, Gu, Wenjing, and Wang, Guangyuan
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ASSOCIATION rule mining ,NATURAL language processing ,GAS explosions ,EMERGENCY management ,EMERGENCIES - Abstract
Emergency case reasoning is essential to emergency management. In this paper, we propose a novel emergency case reasoning method based on fuzzy cognitive map (FCM), to model the inherent causal relationships in emergency cases. Specifically, we first obtain emergency domain elements and mine their association rules, by leveraging natural language processing technology and FT-Growth dada mining algorithm. We then design an effective algorithm to learn causal knowledge links from the gathered association rules. Finally, we construct an FCM regarding emergency events and show the reasoning process. Experiments on the gas explosion demonstrate that the proposed method can successfully model the internal causal relationships of emergency elements, and the development of the emergency event can be reflected by the reasoning process of the proposed method according to its varying variables of state. The proposed method can effectively inference and predict the tendency of emergency cases based on the reasoning process, which can further provide valuable decision supports to emergency responders. [ABSTRACT FROM AUTHOR]
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- 2019
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231. A hybrid inconsistent sustainable chemical industry evaluation method.
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Han, Ying, Lu, Zhenyu, and Chen, Sheng
- Subjects
MULTIPLE criteria decision making ,CHEMICAL industry ,EVALUATION methodology ,CHEMICAL process industries ,ENVIRONMENTAL protection - Abstract
Depletion of energy and environment pollution problems are the unprecedented challenges faced by the conventional chemical industry in China. The ever-growing awareness of energy and environment protection makes sustainable development increasingly play the crucial role in China's chemical industry. Most existing methods about chemical industry evaluation are economic-oriented, which neglect the environmental and social issues, especially conflicts among them. This paper develops a novel hybrid multiple criteria decision making framework under bipolar linguistic fuzzy environment based on VIKOR and fuzzy cognitive map to evaluate sustainable chemical industry. The new method captures the characteristics of uncertainty, inconsistency and complexity in the evaluation process of sustainable chemical industry. Meanwhile, combination of fuzzy cognitive map technique makes the new method consider not only the importance but also the interrelations about criteria and obtain better insight into sustainable chemical industry evaluation. A case study and comparison analysis with existing methods reflect the new proposed framework is more suitable to the needs of environment and energy protection in the sustainable chemical industry. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
232. Study on logistics demand forecasting model based on fuzzy cognitive map.
- Author
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HAN Huijian, HAN Jiabing, and ZHANG Rui
- Abstract
Accurate prediction of social logistics demands is essential to government5s policy formulation for the logistics industry as well as to enterprise's logistics activity planning. In this paper, a logistics demand prediction model construction method based on the fuzzy cognitive map (FCM) is proposed. This method comprehensively considers the mutual influence between five economic elements (GDP, total import and export volume, etc.) and logistics demands, and acquires the mutual influence weight through machine learning of historical data. Finally, a logistics demand prediction model is built, which can realize accurate prediction of the future logistics demands. The experimental results provide solid evidence for high precision and favorable performance of the model in predicting logistics demands. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
233. Analysis of an evolutionary algorithm for complex fuzzy cognitive map learning based on graph theory metrics and output concepts.
- Author
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Poczeta, Katarzyna, Kubuś, Łukasz, and Yastrebov, Alexander
- Subjects
- *
FUZZY graphs , *COGNITIVE learning , *GRAPH theory , *EVOLUTIONARY algorithms , *FUZZY algorithms , *DECISION support systems , *LEARNING - Abstract
Abstract The fuzzy cognitive map (FCM) is an effective tool for modeling dynamic decision support systems. It describes the analyzed phenomenon in the form of key concepts and the causal connections between them. The main aspects of the building of the FCM model are: concepts selection, determining the output concepts, criterion selection, and determining the relationships between concepts. It is usually based on expert knowledge. The main goal of the paper is to define the optimal in some sense FCM structure through the introduction of the notion of output concepts and minimizing the number of concepts and connections between them. The proposed approach allows for: (1) the selection of key concepts based on graph theory metrics and determining the connections between them; (2) the determination of the criterion of learning based on output concepts and fitting the learning process to the analyzed problem. A simulation analysis was done with the use of synthetic and real-life data. Experiments confirm that the proposed approach improves the learning process compared to the standard approaches. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
234. Measuring public acceptance of climate-friendly technologies based on creativity and cognitive approaches: Practical guidelines for reforming risky energy policies in Iran.
- Author
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Fetanat, Abdolvahhab, Shafipour, Gholamreza, and Mohtasebi, Seyedeh-Maryam
- Subjects
- *
CLIMATE change , *FOSSIL fuels , *RENEWABLE energy sources , *CLEAN energy , *WATER heaters - Abstract
Abstract In order to mitigate climate change and reduce fossil fuel dependency in Iran, the government of the country has announced its renewable energy policies to increase the use of renewable energies, but the share of the energy generation mix of Iran is very low due to the lack of public acceptance. These challenges continue and can be hard to overcome at all levels. This paper investigates this problem at regional level by measuring public acceptance towards development of climate-friendly technologies in order to provide required feedbacks to policy-makers of the government for ushering changes in their policies already made or in their executing mechanism, possibly deducting future risks such as public opposition from their end and improving the level of acceptance. This study uses a mixed-methods analytical approach for quantitatively taking that level, including creativity techniques and fuzzy cognitive maps (FCMs). FCMs could directly map out policy-makers' cognitions on the problem. This study provides the mathematical formulation of the problem with its conceptual interpretation to import policy-makers' knowledge into FCMs when the knowledge is gained explicitly with creativity techniques. The authors focused on a case of Solar Water Heater adoption in the city of Behbahan in Khuzestan Province. Graphical abstract Image Highlights • A combinative method for measuring public acceptance of clean energy technologies is proposed. • It provides the mathematical formulation of the acceptance problem with its conceptual interpretation. • It focused on a case study of solar water heater adoption in Iran. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
235. Research on early warning and monitoring algorithm of financial crisis based on fuzzy cognitive map.
- Author
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Wang, Qian, Hui, Fengting, Wang, Xin, and Ding, Qi
- Subjects
- *
FINANCIAL crises , *SECURITY systems , *WARNINGS , *ALGORITHMS - Abstract
Because the financial crisis early warning and monitoring is too complex, most of the current implementation can only alternately choose early warning in accordance with the criteria of monitoring the financial crisis. As a result, the security measures are not in accordance with the actual situation of the system, and cannot be adjusted quickly according to the changes of the system. This paper presents a financial crisis early warning detection algorithm based on fuzzy cognitive map. The relationship between financial data is obtained by fuzzy cognitive map, and the system crisis value is calculated by fuzzy cognitive map reasoning process. Finally, through the financial data of listed companies, the early warning and monitoring effect of the algorithm is verified. The experimental results show that the method is efficient, cost-effective, and can timely and reasonably reflect the crisis state of financial data. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
236. Iterative generation of insight from text collections through mutually reinforcing visualizations and fuzzy cognitive maps.
- Author
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Pillutla, Venkata Sai and Giabbanelli, Philippe J.
- Subjects
VISUAL environment ,GENERATIONS - Abstract
Abstract Developing a comprehensive explanation of complex social phenomena is a difficult task that analysts often have to perform using vast collections of text documents. On the one hand, solutions exist to assist analysts in creating causal maps from text documents, but these can only articulate the relationships at work in a problem. On the other hand, Fuzzy Cognitive Maps (FCMs) can articulate these relationships and perform simulations, but no environment exists to help analysts in iteratively developing FCMs from text. In this paper, we detail the design and implementation of the first tool that allows analysts to develop FCMs from text collections, using interactive visualizations. We make three contributions: (i) we combine text mining and FCMs, (ii) we implement the first visual analytics environment built on FCMs, and (iii) we promote a strong feedback loop between interactive data exploration and model building. We provide two case studies exemplifying how to create a model from the ground-up or improve an existing one. Limitations include the increase in display complexity when working with large collection of files, and the reliance on KL-divergence for ad-hoc retrieval. Several improvements are discussed to further support analysts in creating high-quality models through interactive visualizations. Highlights • A new approach to combine Fuzzy Cognitive Mapping and Text Mining is proposed. • The approach allows to use qualitative evidence to quickly create mental models. • Design choices are highlighted and contrasted with related visual environments. • The approach is exemplified on two case studies with real-world data. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
237. Mapping the influences of resilience engineering on health, safety, and environment and ergonomics management system by using Z‐number cognitive map.
- Author
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Zarrin, Mansour and Azadeh, Ali
- Subjects
ERGONOMICS ,FUZZY logic ,INDUSTRIAL safety - Abstract
This study evaluates and analyzes the impacts of resilience engineering (RE) principles on integrated health, safety, environment, and ergonomics (HSEE) management system. In decision sciences, information should be reliable due to uncertainty and vagueness existing in information. To this end, in this study, the concept of Z‐numbers with fuzzy cognitive map (FCM) approach is integrated and a novel approach named Z‐number cognitive map is proposed. The main advantages of the proposed approach are determination of the weighted causality relations (for employing FCM) as well as handling uncertainty (for considering Z‐numbers concept). This approach is used to show the effects of RE indicators on HSEE management system. The required data for the proposed approach is collected from a large petrochemical plant by distributing questionnaires. According to the results, the RE principles have significant impact on HSEE management system. Top management commitment, learning, preparedness and awareness have the most impacts on environment, health, ergonomics and safety factors, respectively. This is the first study that employs Z‐number cognitive map for evaluating and improving the impacts of RE on HSEE factors in a large petrochemical plant. The proposed approach in this study, can help managers of various safety‐critical systems to improve their performance in terms of HSEE factors using RE concept. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
238. How to promote a new and sustainable food consumption model: A fuzzy cognitive map study.
- Author
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Morone, Piergiuseppe, Falcone, Pasquale Marcello, and Lopolito, Antonio
- Subjects
- *
SUSTAINABLE development , *FOOD consumption , *FUZZY logic , *ENERGY economics , *EMISSIONS (Air pollution) - Abstract
Abstract The amount of food wastage produced at the global level generates high environmental, economic and social costs, such as greenhouse gas emissions, soil degradation, waste generation, consumption of natural resources, as well as economic losses, inequality and poverty. Taking stock of these problems, this paper conducts an empirical investigation in order to identify and recommend the most effective policy actions and private initiatives that might modify the current unsustainable food consumption model, characterizing high income countries, in order to achieve a significant reduction in the amount of food wastage. Specifically, it performs a fuzzy inference simulation by means of a three-step methodology: analyzing the use of language within the food waste reduction/valorization debate to identify system variables; deducing the map of causal-effect relationships among the identified system variables through interviews to a pool of experts; and finally, performing a fuzzy inference simulation, to identify drivers potentially able to discourage current unsustainable consumer behaviors. Among other things, the fuzzy analysis shows how some policy drivers, as "Public food waste rules", "Investments and infrastructure" and "Small-scale farming" are particularly effective in supporting a new and sustainable food consumption model. At the same time, the experts' knowledge allows highlighting the crucial role of "biorefinery" in fostering a transition towards a sustainable consumption model. This is an interesting result, as it points at the ability of biorefineries to enhance a general positive attitude of consumers which, in turn, would translate into more sustainable consumption practices. Highlights • Effective policy drivers and private initiatives to reduce the amount of food waste are identified. • Food waste system variables are elicited by means of discourse analysis. • Fuzzy inference is employed to investigate the causal-effect map derived from experts' knowledge. • Side-effects should be considered in designing policy interventions. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
239. Designing a fuzzy cognitive map to evaluate drilling and blasting problems of the tunneling projects in Iran.
- Author
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Bakhtavar, E. and Shirvand, Y.
- Abstract
The study of drilling and blasting processes in excavation projects, especially in Iran, demonstrates various challenges and problems that eventually affect the technical and economic aspects of project performance. This paper introduces a methodology based on a computer-based fuzzy cognitive map approach to find and prioritize the problematic drilling and blasting factors in tunneling projects in Iran. A particular cognitive map of the problem was designed by use of 34 problematic factors that selected by tunneling engineers in Iran. In the designed map, the weights of the problematic factors and their interactions were considered on the basis of the opinions of engineers. The designed map was finally solved by considering the causes and effects of the problematic factors. Results indicated that the most critical factors were respectively identified as the disregard for geomechanical changes, the lack of accurate drilling supervision and management, and the insufficient knowledge of blasting teams. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
240. Effective Brain Connectivity for fNIRS With Fuzzy Cognitive Maps in Neuroergonomics
- Author
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Mehrin Kiani, Javier Andreu-Perez, Elpiniki I. Papageorgiou, Mukesh Prasad, Hani Hagras, and Chin-Teng Lin
- Subjects
General linear model ,Computer science ,Brain activity and meditation ,business.industry ,Dynamic causal modelling ,Pattern recognition ,Cognition ,02 engineering and technology ,Fuzzy cognitive map ,Quantitative measure ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,Neuroergonomics ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,030217 neurology & neurosurgery ,Software - Abstract
Effective connectivity (EC) amongst functional near-infrared spectroscopy (fNIRS) signals is a quantitative measure of the strength of influence between brain activity associated with different regions of the brain. Evidently, accurate deciphering of EC gives further insight into the understanding of the intricately complex nature of neuronal interactions in the human brain. This work presents a novel approach to estimate EC in the human brain signals using enhanced fuzzy cognitive maps (FCMs). The proposed method presents a regularized methodology of FCMs, called effective FCMs (E-FCMs), with improved accuracy for predicting EC between real, and synthetic fNIRS signals. Essentially, the revisions made in the FCM methodology include a more powerful prediction formula for FCM combined with independent tuning of the transformation function parameter. A comparison of EC in fNIRS signals obtained from E-FCM with that obtained from standard FCM, general linear model (GLM) parameters that power Dynamic Causal Modelling (DCM), and Granger Causality (GC) manifests the greater prowess of the proposed E-FCM over the aforementioned methods. For real fNIRS data, an empirical investigation is also made to gain an insight into the role of oxyhemoglobin and deoxyhemoglobin (oxy-Hb, deoxy-Hb) in representing the cognitive activity. We believe this work has profound implications for neuroergonomics research communities.
- Published
- 2022
241. Implementation of Fuzzy Cognitive Map and Support Vector Machine for Classification of Oral Cancers.
- Author
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Anuradha, K. and Uma, K. P.
- Subjects
SUPPORT vector machines ,ORAL cancer ,CANCER diagnosis ,CELL growth - Abstract
Objective: Tumors at any stage may progress into cancer. Till now, cancer classification is a challenging task for the researchers. Research on the cancer biology starts with the changes in the tissues. Oral cancer is a malignant cell growth in the oral cavity. Method: The proposed work combines Fuzzy Cognitive map (FCM) with Support Vector Machine (SVM) for grading oral tumor. The histological features are used as concepts and the interrelationships between the concepts are identified. FCM acts as a classifier to distinguish between benign and malignant cases. Further, the extracted output from FCM is fed as an input to the Support Vector Machine (SVM) classifier. This will improve the prediction capabilities. Result: The classification accuracy obtained for the proposed model is 92.10% for malignant cases and 94.11% for benign cases. Conclusion: The experimental results show that the combination of FCM with SVM obtained a good result when compared to the hybrid model using FCM. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
242. Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector.
- Author
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Choi, Youngseok, Lee, Habin, and Irani, Zahir
- Subjects
- *
BIG data , *COGNITIVE maps (Psychology) , *PUBLIC sector , *DATA analytics , *INFORMATION technology - Abstract
The prevalence of big data is starting to spread across the public and private sectors however, an impediment to its widespread adoption orientates around a lack of appropriate big data analytics (BDA) and resulting skills to exploit the full potential of big data availability. In this paper, we propose a novel BDA to contribute towards this void, using a fuzzy cognitive map (FCM) approach that will enhance decision-making thus prioritising IT service procurement in the public sector. This is achieved through the development of decision models that capture the strengths of both data analytics and the established intuitive qualitative approach. By taking advantages of both data analytics and FCM, the proposed approach captures the strength of data-driven decision-making and intuitive model-driven decision modelling. This approach is then validated through a decision-making case regarding IT service procurement in public sector, which is the fundamental step of IT infrastructure supply for publics in a regional government in the Russia federation. The analysis result for the given decision-making problem is then evaluated by decision makers and e-government expertise to confirm the applicability of the proposed BDA. In doing so, demonstrating the value of this approach in contributing towards robust public decision-making regarding IT service procurement. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
243. A hybrid intelligent model for assessment of critical success factors in high-risk emergency system.
- Author
-
Han, Yuzhen and Deng, Yong
- Abstract
High-risk emergency systems are emerging as a new generation technology to prevent disasters. Latest research points out that these systems could protect properties and lives in an efficient way. Limited to the sources, the feasible way to improve the performance of the system is to identify critical success factors (CSFs) and then optimize them. In this paper, a multi-criteria decision-making (MCDM) approach integrating Affinity Diagram, Decision Making Trial and Evaluation Laboratory (DEMATEL), fuzzy cognitive map (FCM) and Dempster-Shafer evidence theory (evidence theory) is proposed to identify critical success factors in high-risk emergency system. The DEMATEL and FCM are initially combined to tackle the decision-making problem in theory and practice. This model has ability to fuse technical, economic, political and social attributes. The proposed method is applied to select CSFs for Chongqing city. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
244. An integrated assessment of food waste model through intuitionistic fuzzy cognitive maps.
- Author
-
Emir, Oğuz and Ekici, Şule Önsel
- Subjects
- *
FOOD waste , *FOOD industrial waste , *COGNITIVE maps (Psychology) , *WASTE minimization , *WASTE management , *NATURAL resources - Abstract
In recent years, the waste management field has received substantial attention from policymakers, organizations, academics, and researchers due to increased focus on sustainability and carbon footprint reduction as well as concerns around rapid depletion of natural resources, public health, and environmental impact. Studies on food waste management have become especially important given the dramatic growth of the world's population and global hunger and malnutrition crisis. Considering the fact that one-third of the world's food supply is wasted or lost annually while hundreds of millions of people are living with food insecurity, it is easy to understand the importance of research studying appropriate food waste management actions for sustainability. Since the subject of food waste involves complicated linkages, the determination of a suitable model is pivotal. Integrated assessment models (IAMs) have been commonly used to uncover hidden patterns and present insights to policymakers. Furthermore, these models are well-designed to integrate data, information, and multidisciplinary knowledge into a single framework. This project presents a Fuzzy Cognitive Map (FCM) extended with intuitionistic fuzzy sets using the documentary coding method. This intuitionistic FCM (iFCM) is used to analyze the primary factors, explore the interactions between food waste factors, and prioritize some policies to reduce food waste by incorporating hesitancy weight factors representing the lack of information. Then several what-if scenario analyses are generated to review the interrelationships between factors in the developed model and facilitate a decision-making process for researchers. Eventually, it is concluded that food waste reduction is achievable with the implementation of the right policies, and this also improves the other concepts such as the intention not to food waste, shopping routines, and planning routines. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
245. ASSESSMENT OF RISKS OF DECREASE IN QUALITY OF PROFESSIONAL TRAINING WITH USE OF A METHOD OF COGNITIVE MODELING
- Author
-
Alexander I. Mitin and Tatyana A. Filicheva
- Subjects
educational system ,risks ,fuzzy cognitive map ,professional education ,information-analytical system ,monitoring ,information support ,Special aspects of education ,LC8-6691 - Abstract
In article the method, allowing to analyze risks of decrease in quality of professional training on the basis of the developed cognitive map (the weighed oriented graph of concepts and relations between them), formalizing expert estimates is offered. Realization of the offered method within information-analytical system of monitoring of quality as subsystem of the general information system of educational institution is described.
- Published
- 2016
- Full Text
- View/download PDF
246. Параметрическое управление развитием сельского хозяйства на основе когнитивного моделирования
- Subjects
параметрическое управление ,социально-экономическая система ,socio-economic system ,сельское хозяйство ,нечеткая когнитивная карта ,аграрный рост ,fuzzy cognitive map ,parametric control ,когнитивное моделирование ,agricultural growth ,cognitive modeling ,agriculture - Abstract
С использованием концепции параметрического управления сформирована доказательная база по идентификации противоречия между увеличением объема производства сельскохозяйственной продукции и отсутствием условий для расширенного воспроизводства в отрасли, что выступает основным ограничением национального аграрного роста. Конкретизированы теоретические основы параметрического управления социально-экономическими системами и обосновано введение в процесс управления этапа параметризации управляемой системы. Указано, что выбор управленческого решения определяется на основе сопоставления оценки двух блоков параметров – потенциала внешнего управленческого воздействия и внутреннего потенциала управляемой системы. Сравнительное несоответствие результатов параметризации свидетельствует о наличии противоречия в процессе управления и определяет необходимость корректировки управленческого решения. Инструментальной основой для определения содержания противоречия в управлении развитием сельского хозяйства явились технологии нечеткого когнитивного моделирования. С применением экспертных оценок и корреляционно-регрессионного анализа на основе статистических данных за период 2000–2020 гг. была осуществлена параметризация сельского хозяйства в форме нечеткой когнитивной карты. Структурно-целевой анализ и расчет системных показателей когнитивной карты позволил выявить основные ограничения в развитии процессов аграрной динамики. Результаты когнитивного моделирования сценариев управления аграрным развитием показали, что потенциал управленческих действий по отношению к сельскому хозяйству не формирует адекватный уровень потенциала аграрного роста. Соответственно, обоснована необходимость изменения подходов к управлению сельским хозяйством для достижения устойчивости и сбалансированности аграрной динамики в долгосрочной перспективе., The concept of parametric control is used to prove the existence of a contradiction between the growth of agricultural production and the lack of conditions for expanded reproduction in Russian agriculture. This contradiction is the main limitation of agricultural growth in the country. The theoretical foundations of parametric control are specified for socio-economic systems and the parameterization stage of the controlled system is included in the control process. A control action should be chosen by comparing the estimates of two blocks of parameters. The first block assesses the potential of an external control action affecting the system. The second block of parameters shows the internal potential of the controlled system. If the estimates do not match, the control process has a contradiction, and the control action should be corrected. Fuzzy cognitive modeling is used to determine the contradiction in the control of agricultural development. A fuzzy cognitive map of Russian agriculture is constructed using expert assessments and correlation-regression analysis according to statistical data for the period 2000–2020. The structural-target analysis of this map is performed and its system indicators are calculated to identify the main limitations in agricultural dynamic processes. Agricultural development is forecasted through the scenario analysis of the fuzzy cognitive map. According to the cognitive modeling results, the control action potential exceeds the agricultural growth potential. Therefore, for sustainable long-term agricultural growth in Russia, it is necessary to change approaches to agricultural management., Проблемы управления, Выпуск 3 2023, Pages 20-39
- Published
- 2023
- Full Text
- View/download PDF
247. Time series prediction based on high-order intuitionistic fuzzy cognitive maps with variational mode decomposition
- Author
-
Yao Xixi, Luo Chao, and Ding Fengqian
- Subjects
Nondeterministic algorithm ,Sequence ,Series (mathematics) ,Computer science ,Particle swarm optimization ,Computational intelligence ,Geometry and Topology ,Time series ,Representation (mathematics) ,Algorithm ,Software ,Fuzzy cognitive map ,Theoretical Computer Science - Abstract
In reality, time series subject to the internal/external influence are usually characterized by nonlinearity, uncertainty, and incompleteness. Therefore, how to model the features of time series in nondeterministic environments is still an open problem. In this article, a novel high-order intuitionistic fuzzy cognitive map (HIFCM) is proposed, where intuitionistic fuzzy set (IFS) is introduced into fuzzy cognitive maps with temporal high-order structure. By means of IFS, the ability of model for the representation of uncertainty can be effectively improved. In order to capture the fluctuation features of series data, variational mode decomposition is utilized to decompose time series into sequences of various frequencies, based on which fine feature structures on different scales can be obtained. Each concept of HIFCM corresponds to one decomposed sequence such that casual reasoning can be achieved among the obtained features in various frequencies of time series. All parameters are learned by the particle swarm optimization algorithm. Finally, the performance of the method is verified on the public datasets, and experimental results show the feasibility and effectiveness of the proposed method.
- Published
- 2021
248. MENTA: how to balance authorial intention and user agency in virtual environments
- Author
-
Lourdeaux, Domitile, Sallak, Mohamed, Lacaze-Labadie, Rémi, Lourdeaux, Domitile, Appel à projets générique - Agents virtuels émotionnels, adaptatifs et sociaux pour la formation d'équipes - - VICTEAMS2014 - ANR-14-CE24-0027 - Appel à projets générique - VALID, and Control of Technological Systems of Systems - - MS2T2010 - ANR-10-LABX-0071 - LABX - VALID
- Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI] ,Planning ,Virtual Environments ,Fuzzy Cognitive Map - Abstract
We aim to create an artificial intelligence based virtual environment to train medical team leaders to rescue injured people after a mass casualty. In this paper, we describe a resilient and adaptive engine, MENTA, to orchestrate dynamically various training situations and various virtual teammates. MENTA is in charge of the narrative control by proposing a set of adjustments that satisfies narrative objectives chosen by the trainer. These adjustments take the form of a prescribed scenario that is generated by MENTA via a planning engine that we have coupled with fuzzy cognitive maps. This approach tackles the problem of a set of objectives that are often contradictory: user agency, authorial intention and resilience.
- Published
- 2022
249. Effects of Uncertainty Shocks on Household Consumption and Working Hours: A Fuzzy Cognitive Map-Based Approach
- Author
-
Yeonggyu Yun and Hye-Young Jung
- Subjects
consumption ,fuzzy cognitive map ,nonlinear Hebbian learning ,uncertainty shock ,working hours ,Mathematics ,QA1-939 - Abstract
This paper aims to model an individual’s decision-making process in relation to macroeconomic dynamics that involve a large number of variables, which might inflict dimensionality issue in empirical analysis. We employ the fuzzy cognitive map (FCM) for this purpose, and present a parsimonious approach in assessing the impacts of uncertainty shocks on individual households by constructing FCM where households adjust their consumption and working hours in response to changes in exogenous economic uncertainty. We employ FCM to analyze how uncertainty shocks affect the households’ consumption, working hours, and income sources. We further conduct simulations to examine roles of expansionary fiscal policy in alleviating the negative impacts of uncertainty shocks. Our simulations yield similar results as compared to the existing literature on the impacts of uncertainty shocks. We suggest a hybrid algorithm of constructing FCM, and hence demonstrate the extensibility of FCM in analyzing complex macroeconomic systems.
- Published
- 2020
- Full Text
- View/download PDF
250. A Dynamic Intelligent Policies Analysis Mechanism for Personal Data Processing in the IoT Ecosystem
- Author
-
Konstantinos Demertzis, Konstantinos Rantos, and George Drosatos
- Subjects
Internet of Things ,privacy ,GDPR ,digital consents management ,fuzzy cognitive map ,extreme learning machine ,Technology - Abstract
The evolution of the Internet of Things is significantly affected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR). The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed and unambiguous consent to collect and process the data concerning them. ADVOCATE is an advanced framework that fully complies with the requirements of GDPR, which, with the extensive use of blockchain and artificial intelligence technologies, aims to provide an environment that will support users in maintaining control of their personal data in the IoT ecosystem. This paper proposes and presents the Intelligent Policies Analysis Mechanism (IPAM) of the ADVOCATE framework, which, in an intelligent and fully automated manner, can identify conflicting rules or consents of the user, which may lead to the collection of personal data that can be used for profiling. In order to clearly identify and implement IPAM, the problem of recording user data from smart entertainment devices using Fuzzy Cognitive Maps (FCMs) was simulated. FCMs are an intelligent decision-making system that simulates the processes of a complex system, modeling the correlation base, knowing the behavioral and balance specialists of the system. Respectively, identifying conflicting rules that can lead to a profile, training is done using Extreme Learning Machines (ELMs), which are highly efficient neural systems of small and flexible architecture that can work optimally in complex environments.
- Published
- 2020
- Full Text
- View/download PDF
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