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Abstract: Advanced neuro-fuzzy modeling, namely an adaptive network-based fuzzy inference system (ANFIS), was employed to develop models for the prediction of suspended solids (SS) and chemical oxygen demand (COD) removal of a full-scale wastewater treatment plant treating process wastewaters from a paper mill. In order to improve the network performance, fuzzy subtractive clustering was used to identify model''s architecture and optimize fuzzy rule, meanwhile principal component analysis (PCA) was applied to reduce the input variable dimensionality. Input variables were reduced from six to four for COD and SS models, by considering PCA results and linear correlation matrices among input and output variables. The results indicate that reasonable forecasting and control performances have been achieved through the developed system. The minimum mean absolute percentage errors of 1.003% and 0.5161% for CODeff and SSeff could be achieved using ANFIS. The maximum correlation coefficient values for CODeff and SSeff were 0.9912 and 0.9882, respectively. The minimum mean square errors of 1.2883 and 0.0342, and the minimum RMSEs of 1.135 and 0.1849 for CODeff and SSeff could also be achieved. [Copyright &y& Elsevier]

This paper investigates the potential impact of green fuel adoption on the Saudi Arabian maritime industry using fuzzy set theory. We will examine the cost-profitability of green fuel adoption and its implications for the Saudi Arabian economy. By employing fuzzy set theory, we can more accurately predict and analyze the potential impacts of green shipping. This paper will present case studies from the shipping industry that have successfully used fuzzy set theory to optimize green fuel usage and profitability. Moreover, this paper will focus on the use of green fuels as a way of reducing the environmental impacts of the shipping industry in Saudi Arabia. This paper will explore the impact of fueling ships with green fuel in Saudi Arabia and use fuzzy set theory to analyze the cost-profitability of this action. [ABSTRACT FROM AUTHOR]

We propose a new concept which is a generalization of fuzzy soft subset and fuzzy soft equal. Using such notions, we will be able to consider the distributive law of fuzzy soft sets. Using the distributive law of fuzzy soft sets, we point out that the distributive law of trapezoidal fuzzy soft sets as proposed by Xiao et al. (2012) is not true. The correction will further improve further extensions of the results of Xiao et al. (2012). We will also establish the generalized distributive law of trapezoidal fuzzy soft sets along with illustrative examples. [ABSTRACT FROM AUTHOR]

In the recent era, Transportation considers the most powerful component of the business logistics system. Likewise, there is an interdependent relationship between the transportation and logistics systems. This paper aims to make a comparative study of logistics transportation problems based on intelligence algorithms. The researchers surveyed the previous studies conducted in the Artificial Intelligent field to solve complex problems. In this research study, the authors focused on techniques that are mostly applied in transportation and logistics systems, especially, Artificial Neural Network, Genetic Algorithm, and Fuzzy Logic models. Also, a proposed model and algorithm was done to obtain customers' and organizations' satisfaction. Artificial Neural Network uses as a decision tool that combines the system stat sets and the operation state-dependent sets. As well, the genetic algorithm combines the best parameters as a method to finds the best evaluation solutions. And fuzzy logic uses a fuzzy set to help decision-makers in making the best decisions in multiple fields. Finally, authors recommended to work in two new areas which are FGA, NFGA Algorithms to solve complex and multimodal problems that faces transportation logistics sector. [ABSTRACT FROM AUTHOR]

There are many schools of Chinese martial arts routines and complex movements; research on this topic is more geared toward Taijiquan (a kind of traditional Chinese shadow boxing), which is a more well-known type of martial arts. Therefore, the purpose of this paper is to visually analyze the research of Chinese martial arts routines based on the knowledge graph method and to propose a knowledge graph method based on the fuzzy set theory, which is called the transF model throughout this paper. The transF model used the fuzzy relational operation of vectors to not only reduce the computational complexity, but to also better integrate multi-dimensional data, especially when the training set is not particularly sufficient. For the visual analysis of Chinese martial arts routines, this paper selected the 16-year data from 2005 to 2020 as the analysis sample, analyzed high-yield institutions and high-yield authors, and conducted a centrality analysis of the whole dataset. From the structure of the knowledge graph, traditional martial arts are the core part of Chinese martial arts, with a centrality of 0.14. Competitive martial arts are the main branch of Chinese martial arts and the third core after Tai Chi and traditional martial arts, with a centrality of 0.41, which is higher than that of traditional martial arts. This shows its importance in martial arts research. [ABSTRACT FROM AUTHOR]

The design for large-scale offshore systems like renewable energy systems as well as ship structures represents the key factor for the investigation and application of such devices. The existing guide for design schemes of offshore systems cannot cover novel large-scale design demand for recent offshore systems, as a result of the fast-growing scale of offshore systems but the late update of guides. To this end, this paper proposes a novel risk estimation approach of alternative design schemes for large-scale offshore systems as a basis to support the design scheme determinations. Initially, the risks of design schemes are analyzed by fault tree analysis. Subsequently, Bayesian networks and fuzzy sets are employed to calculate the reliability of alternative designs that comply with, or deviate from, the existing guides. The risk level of alternative designs is assessed to ensure the better performance of alternative design schemes in terms of safety. The Bayesian network approach proposed also accretions the weak links in the alternative designs. The results of this paper contribute to enhancing the survivability of offshore systems, such as renewable energy systems as well as ship structures. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy and society, the innovation of grassroots social governance has become increasingly important. This paper constructs 35 grassroots social governance innovation samples. Using the TOE theoretical framework and a fuzzy set qualitative comparative analysis (fsQCA), this paper analyzes the joint effects and interactive relationships of multiple factors on grassroots social governance innovation performance from three dimensions: technology, organization, and environment. The research reveals that internal environmental openness is a necessary condition for achieving high innovation performance in grassroots social governance, and proposes four grouping models that affect the performance of grassroots social governance innovation. This paper explores the inner logic of grassroots social governance innovation from a histological perspective, and on this basis proposes an adaptive path to enhance the performance of grassroots social governance innovation. [ABSTRACT FROM AUTHOR]

This paper discussed the fuzzy reliability of pulping system in paper industry. Pulping system consists of four subsystems such as Digester, Knotter, Deckers, and Openers. These subsystems are working in series. In subsystems Knotter and Openers, one unit is operative and another unit is kept as cold standby. Fuzzy failure rates and fuzzy repair rates of the subsystems are taken as general. Trapezoidal fuzzy numbers are used to find out the reliability of the pulping system. Using Mehar’s method, the numerical results for reliability are obtained by considering exponential, Rayleigh, and Weibull distributions. On the basis of the results obtained in this study, it is suggested that paper industry management should involve Weibull distributed random variables for pulping system to attain higher reliability. [ABSTRACT FROM AUTHOR]

Relieving the emotions of the public through government response is an important part of government emergency management. How governments respond in different situations can avoid stimulating negative emotions during emergencies? This paper analyzes the problem from the perspective of configuration; that is, this paper explores the combined effects of multiple factors on emotions. We construct the theoretical framework "Situation-Responder-Content" from situation, responder and response content, and use the government microblogs (n= 1517) from 23 major production accidents in China for the discussion with the use of fuzzy set qualitative comparison analysis (fsQCA). According to the results, the effective response types of different agencies in emergencies are summarized. Local authorities can respond in ways that include "Measures type" and "Measures-Emotion type". Functional agencies can respond through "Measures type", "Measures-Emotion type" and "Government feature-Driven" type. This study emphasizes that government response in emergencies is a systematic process. Responsive agencies need to release effective information on the basis of fully considering the situation and other factors. Configuration analysis should also be an important direction in government response research, which is helpful to the practice of government response in emergencies. [ABSTRACT FROM AUTHOR]

Debt restructuring is an effective means to solve the financial difficulties of enterprises. At present, the operation methods and means of enterprises with different characteristics to participate in debt restructuring are different, and no universal debt restructuring scheme has been formed. In order to solve this problem, this paper uses the method of fuzzy set qualitative comparative analysis. This paper discusses the influence mechanism of multiple concurrent factors on enterprise debt restructuring and summarizes the selection rules of debt restructuring strategies for enterprises with different characteristics of debt. The research shows that there are five kinds of allocation for enterprises to realize debt restructuring. According to the different core conditions, enterprise debt restructuring can be divided into high-quality operation and management mode, technology leading mode, and debt-to-equity mode. The research results reveal the mechanism behind enterprise debt restructuring and provide a reference basis for the government and creditors to make corresponding decisions in the debt restructuring process. [ABSTRACT FROM AUTHOR]

Infrastructure networks are critical components of contemporary society, and numerous approaches have been suggested for the selection of strategies to protect these networks. However, for uncertain environments, research on attack and defense game models for infrastructure networks is limited. Therefore, after reviewing the existing approaches, a method based on interval-valued intuitionistic fuzzy set (IVIFS) theory is proposed for attack and defense games in critical infrastructure networks. First, we present the process of constructing the game model proposed in this paper, which mainly includes the formulation of the cost model, the strategies, and the method of generating IVIFS payoffs. Next, the Nash equilibria of the game are identified by a pair of nonlinear programming models based on IVIFS theory. Finally, experiments are conducted on a target scale-free network, and an investigation into the variation patterns of the Nash equilibria under different circumstances is also conducted. We provide explanations for these variation patterns by considering payoffs from the perspective of mathematical programming models. Furthermore, we find that compared to the existing attack and defense game model with crisp payoffs, the model proposed in this paper leads to superior Nash equilibria. Our work is a preliminary attempt to analyse attack and defense games for infrastructure networks based on IVIFS theory, providing a method for assessing payoffs in uncertain environments for the attacker and defender. This topic deserves further study. [ABSTRACT FROM AUTHOR]

Fuzzy sets possess remarkable abilities in expressing and handling information uncertainty, which has resulted in their widespread application in various fields. Nevertheless, distance measurement between IFSs for quantitating their differences and levels of differentiation has remained an open problem that deserves attention. Despite the development of various metrics, they either lack intuitive insight or do not satisfy the axioms of distance measurement, leading to counterintuitive results. To address these issues, this paper proposed a distance measurement method based on Clark divergence, which satisfies the distance measurement axioms and exhibits nonlinearity. Numerical examples demonstrate that our method effectively distinguishes different indicators, yielding more reasonable results. Moreover, when comparing relative differences of the results, our method demonstrated superior adaptability to complex environmental decision-making, providing decision-makers with more accurate and confidential judgments. In our numerical and pattern classification application tests, we achieve an accuracy of 98%, a 40% increase in computing time efficiency and a relative diversity improvement of 35%. The pattern classification algorithm designed in this paper will offer a promising solution to inference problems. [ABSTRACT FROM AUTHOR]

It is widely known that symmetry does exist in management systems, such as economics, management, and even daily life. In addition, effective and qualified decision-making methods can enhance the performance and symmetry of management systems. Hence, this paper focuses on a decision-making method. Linguistic interval-valued q-rung orthopair fuzzy sets (LIVq-ROFSs) have recently been proposed as being effective in describing decision-makers' evaluation values in complex situations. This paper proposes a novel multi-attribute group decision-making (MAGDM) method with LIVq-ROFSs to handle realistic decision-making problems. The main contributions of this study are three-fold. First, a new method for determining the weight information of attributes based on decision makers' evaluation values is proposed. Second, the classical TODIM is extended into LIVq-ROFSs and a new decision-making method is proposed. Third, our proposed MAGDM method is applied to a real decision-making problem to reveal its effectiveness. [ABSTRACT FROM AUTHOR]

China is at a critical moment of transforming high-speed development to high-quality development, and it is significant to improve the efficiency of green technological innovation. In this paper, under the perspective of two-stage innovation value chain, we construct the evaluation index system of green technology innovation efficiency, adopt the super efficiency SBM model to measure the green technology innovation efficiency of China's high-tech industries, and based on the results obtained, we assume the fuzzy set qualitative comparative analysis method (fs-QCA) based on the group theory to explore the complex causal mechanism and grouping paths of the interaction between enterprises, government and market that affects the green technology innovation efficiency Mechanism and group path. The study results show that (1) enterprise, government, and market are not necessary conditions to influence the efficiency of green technological innovation, and even if a particular party plays a central role, it needs the assistance of other parties. (2) The improvement of green technological innovation efficiency requires the interaction of enterprises, government, and market, and even if any party does not have the core conditions, it can still produce high green technological innovation efficiency. (3) The path of the "innovative compensation" effect is identified, which indicates that enterprises will generate a high level of green innovation efficiency under sufficient investment brought about by the enterprise scale effect and matched with a good level of economic development. (4) The market economy-led pathway suggests that when the market economy is highly developed, firms do not need environmental regulation and government support to generate efficient levels of green technological innovation. [ABSTRACT FROM AUTHOR]

The rapid development of renewable energy presents challenges to the security and stability of power systems. Aiming at addressing the power system scheduling problem with load demand and wind power uncertainty, this paper proposes the establishment of different error fuzzy sets based on the Wasserstein probability distance to describe the uncertainties of load and wind power separately. Based on these Wasserstein fuzzy sets, a distributed robust chance-constrained scheduling model was established. In addition, the scheduling model was transformed into a linear programming problem through affine transformation and CVaR approximation. The simplex method and an improved differential evolution algorithm were used to solve the model. Finally, the model and algorithm proposed in this paper were applied to model and solve the economic scheduling problem for the IEEE 6-node system with a wind farm. The results show that the proposed method has better optimization performance than the traditional method. [ABSTRACT FROM AUTHOR]

The Circular Economy (CE) is receiving more attention, especially in Industry 4.0 (I4.0). In the face of several ambiguous and uncertain information, fuzzy techniques based on Fuzzy Set Theory (FST) are essential for developing CE strategies. This paper uses bibliometric methods to analyze the characteristics of the authors, nations/regions, institutions of the literature of FST and CE, and the collaborations relations between them, and then summarize the literature on fuzzy techniques in the CE and identify the specific role that FST can play in each stage of CE, its primary effects on the CE's pre-preparation stage, design and production stage, and recycling and reuse stage. Meanwhile, the paper explores the advantages of I4.0 technologies for CE and analyzes the research on the role of fuzzy techniques based on FST for CE and I4.0 technologies. Last but not least, this paper is concluded by summarizing the knowledge gained from the bibliometric and content analyses of the literature and suggesting further research directions of investigation. This research will draw attention to FST's contribution and encourage its advancement in CE and I4.0 technologies. [ABSTRACT FROM AUTHOR]

In papers published in Journal of Civil Engineering and Management, many applications of fuzzy logic can be found. To commemorate the contributions of the fuzzy set theory proposed by Professor Lotfi Zadeh to the fields of civil engineering and construction management, seven papers were selected for this special issue. These papers combined fuzzy set theory with appropriate methods to solve specialized problems in the fields of civil engineering and construction management, and provided good insights for the applications of fuzzy technology in solving problems related to civil engineering and construction management. [ABSTRACT FROM AUTHOR]

Copyright of System Research & Information Technologies / Sistemnì Doslìdžennâ ta Ìnformacìjnì Tehnologìï is the property of Institute for the Applied System Analysis at the NTUU KPI 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.)

Large-scale group decision-making (LSGDM) involves aggregating the opinions of participating decision-makers into collective opinions and selecting optimal solutions, addressing challenges such as a large number of participants, significant scale, and a low consensus. In real-world scenarios of LSGDM, various challenges are often encountered due to factors such as fuzzy uncertainties in decision information, the large size of decision groups, and the diverse backgrounds of participants. This paper introduces a dual fine-tuning-based LSGDM method using an online review. Initially, the sentiment analysis is conducted on online review data, and the identified sentiment words are graded and quantified into a fuzzy data set to understand the emotional tendencies of the text. Then, the Louvain algorithm is used to cluster the decision-makers. Meanwhile, a method combining Euclidean distances with Wasserstein distances is introduced to accurately measure data similarities and improve clustering performances. During the consensus-reaching process (CRP), a two-stage approach is employed to adjust the scores: to begin with, by refining the scores of the decision representatives via minor-scale group adjustments to generate a score matrix. Then, by identifying the scores corresponding to the minimum consensus level in the matrix for adjustment. Subsequently, the final adjusted score matrix is integrated with the prospect–regret theory to derive the comprehensive brand scores and rankings. Ultimately, the practicality and efficiency of the proposed model are demonstrated using a case study focused on the purchase of solar lamps. In summary, not only does the model effectively extract the online review data and enhance decision efficiency via clustering, but the dual fine-tuning mechanism in the model to improve consensus attainment also reduces the number of adjustment rounds and avoids multiple cycles without achieving the consensus. [ABSTRACT FROM AUTHOR]

Based on the configuration theory, this paper discusses the multiple concurrent causes and causal complex mechanisms affecting the performance differences among different new farmers. Using the fuzzy set qualitative comparative analysis method, taking 40 cases of CCTV’s “ZHI FU JING” column as samples, the paper analyzes the necessary conditions for new farmers to produce high performance by the anthefactory-variable configuration composed of human capital, social capital, psychological capital, entrepreneurial learning and entrepreneurial opportunity identification. The results show that: (1) high human capital is the necessary core condition for new farmers to produce high entrepreneurial performance, lack of high entrepreneurial learning and lack of high entrepreneurial opportunity identification is the core necessary condition for low entrepreneurial performance; (2) the driving mechanism of new farmers’ high entrepreneurial performance is divided into three paths, and the driving mechanism of new farmers’ low entrepreneurial performance is divided into two paths; and (3) the ways of inhibiting new farmers’ performance and promoting their performance are asymmetrical. [ABSTRACT FROM AUTHOR]

When information is incomplete or uncertain, Fermatean hesitant fuzzy sets (FHFSs) can provide more information to help decision-makers deal with more complex problems. Typically, determining attribute weights assumes that each attribute has a fixed influence. Introducing probability information can enable one to consider the stochastic nature of evaluation data and better quantify the importance of the attributes. To aggregate data by considering the location and importance degrees of each attribute, this paper develops a Fermatean hesitant fuzzy multi-attribute decision-making (MADM) method with probabilistic information and an ordered weighted averaging (OWA) method. The OWA method combines the concepts of weights and sorting to sort and weigh average property values based on those weights. Therefore, this novel approach assigns weights based on the decision-maker's preferences and introduces probabilities to assess attribute importance under specific circumstances, thereby broadening the scope of information expression. Then, this paper presents four probabilistic aggregation operators under the Fermatean hesitant fuzzy environment, including the Fermatean hesitant fuzzy probabilistic ordered weighted averaging/geometric (FHFPOWA/FHFPOWG) operators and the generalized Fermatean hesitant fuzzy probabilistic ordered weighted averaging/geometric (GFHFPOWA/GFHFPOWG) operators. These new operators are designed to quantify the importance of attributes and characterize the attitudes of decision-makers using a probabilistic and weighted vector. Then, a MADM method based on these proposed operators is developed. Finally, an illustrative example of selecting the best new retail enterprise demonstrates the effectiveness and practicality of the method. [ABSTRACT FROM AUTHOR]

Multispectral image registration is the process of aligning the spatial regions of two images with different distributions. One of the main challenges it faces is to resolve the severe inconsistencies between the reference and target images. This paper presents a novel multispectral image registration network, Multi-scale Intuitionistic Fuzzy Set Feature-guided Registration Network (IFSrNet), to address multispectral image registration. IFSrNet generates pseudo-infrared images from visible images using Cycle Generative Adversarial Network (CycleGAN), which is equipped with a multi-head attention module. An end-to-end registration network encodes the input multispectral images with intuitionistic fuzzification, which employs an improved feature descriptor—Intuitionistic Fuzzy Set–Scale-Invariant Feature Transform (IFS-SIFT)—to guide its operation. The results of the image registration will be presented in a direct output. For this task we have also designed specialised loss functions. The results of the experiment demonstrate that IFSrNet outperforms existing registration methods in the Visible–IR dataset. IFSrNet has the potential to be employed as a novel image-to-image translation paradigm. [ABSTRACT FROM AUTHOR]

The integration of Distributed Energy Resources utilizing Renewable Energy Sources, Energy Storage Systems, and Information and Communication Technologies is transforming traditional energy systems into adaptable, flexible, and sustainable systems, with the Smart Grid concept playing a pivotal role. This paper surveys intelligent techniques and methods applied in various markets and applications, particularly focusing on their potential adaptation for negotiation processes in Smart Grid contexts. The negotiation mechanisms, crucial for prosumers who engage in real-time transactions, are analyzed with a focus on fuzzy logic tools, specifically q-Rung Orthopair Fuzzy Sets. These tools are evaluated for their capability to handle negotiation tasks and Multi-Criteria Decision-Making problems. The paper proposes a negotiation schema for healthcare buildings, especially hospitals, given their significant environmental impact, providing insight for future research. [ABSTRACT FROM AUTHOR]

Featured Application: The research in this paper can provide a feasible technical means for the assembly sequence optimization of aviation reducers with complex structures, effectively promote the progress of the complex assembly sequence optimization technology of aviation reducers, and realize the comprehensive evaluation of the overall assembly quality and performance index of aviation reducer products. It can be applied to the assembly control of tanks, armored vehicles, ships, and other complex equipment to improve their assembly quality. An assembly sequence evaluation is one of the most important research directions of assembly sequence planning (ASP) for complex mechanical transmission products. Currently, aviation reducers lack a multi-perspective and multi-level evaluation of their assembly sequence. The existing evaluation indicators vary. The evaluation methods have low effectiveness and poor practicability. Therefore, a comprehensive multidimensional evaluation method for complex assembly sequences is proposed in this paper. A multidimensional comprehensive evaluation of the overall assembly quality and performance indices of aviation reducer products is realized. Firstly, the main factors affecting assembly sequence planning are considered: the attributes of the basic unit parts and the cost control of the assembly process. An evaluation index system of assembly sequence planning based on the two dimensions of assembly cost and ontology is constructed. Then, according to the multidimensional evaluation index, fuzzy evaluation theory is used to establish a fuzzy set and a matrix for each dimensional evaluation index. The index weight is divided. A comprehensive evaluation model and the function of each dimension are established. After a comprehensive evaluation, the multidimensional assembly sequence evaluation method for aviation reducers is formed. Finally, the method is applied to the assembly process of the primary reducer of a helicopter's main reducer, and a comprehensive evaluation of its assembly sequence scheme is completed to verify the feasibility of the proposed method. This article constructs a complex assembly sequence evaluation method that includes 12 evaluation indicators, improves the assembly sequence planning evaluation index system of aviation reducers, and can effectively promote the progress of optimization technology for complex assembly sequences of aviation reducers. [ABSTRACT FROM AUTHOR]

Convolutional Neural Networks (CNNs) are a kind of artificial neural network designed to extract features and find out patterns for tasks such as segmentation, recognizing objects, and drawing up classification. Within a CNNs architecture, pooling operations are used until the number of parameters and the computational complexity are reduced. Numerous papers have focused on investigating the impact of pooling on the performance of Convolutional Neural Networks (CNNs), leading to the development of various pooling models. Recently, a fuzzy pooling operation based on type-1 fuzzy sets was introduced to cope with the local imprecision of the feature maps. However, in fuzzy set theory, it is not always accurate to assume that the degree of non-membership of an element in a fuzzy set is simply the complement of the degree of membership. This is due to the potential existence of a hesitation degree, which implies a certain level of uncertainty. To overcome this limitation, intuitionistic fuzzy sets (IFS) were introduced to incorporate the concept of a degree of hesitation. In this paper, we introduce a novel pooling operation based on intuitionistic fuzzy sets to incorporate the degree of hesitation heretofore neglected by a fuzzy pooling operation based on classical fuzzy sets, and we investigate its performance in the context of image classification. Intuitionistic pooling is performed in four steps: bifuzzification (by the transformation of data through the use of membership and non-membership maps), first aggregation (through the transformation of the IFS into a standard fuzzy set, second aggregation (through the transformation and use of a sum operator), and the defuzzification of feature map neighborhoods by using a max operator. IFS pooling is used for the construction of an intuitionistic pooling layer that can be applied as a drop-in replacement for the current, fuzzy (type-1) and crisp, pooling layers of CNN architectures. Various experiments involving multiple datasets demonstrate that an IFS-based pooling can enhance the classification performance of a CNN. A benchmarking study reveals that this significantly outperforms even the most recent pooling models, especially in stochastic environments. [ABSTRACT FROM AUTHOR]

A new methodology for solving the fuzzy multiobjective optimization problems is proposed in this paper by considering the fusion of cooperative game theory and genetic algorithm. The original fuzzy multiobjective optimization problem needs to be transformed into a scalar optimization problem, which is a conventional optimization problem. Usually, the assignments of suitable coefficients to the corresponding scalar optimization problem are subjectively determined by the decision makers. However, these assignments may cause some biases by their subjectivity. Therefore, this paper proposes a mechanical procedure to avoid this subjective biases. We are going to formulate a cooperative game using the α -level functions of the multiple fuzzy objective functions. Under this setting, the suitable coefficients can be determined mechanically by involving the core values of the cooperative game, which is formulated using the multiple fuzzy objective functions. We shall prove that the optimal solutions of the transformed scalar optimization problem are indeed the nondominated solutions of fuzzy multiobjective optimization problem. Since the core-nondominated solutions will depend on the coefficients that are determined by the core values of cooperative game, there will be a lot of core-nondominated solutions that will also depend on the corresponding coefficients. In order to obtain the best core-nondominated solution, we shall invoke the genetic algorithms by evolving the coefficients. [ABSTRACT FROM AUTHOR]

This paper investigates the complex causal relationships between various types of environmental regulatory instruments (ERI) and agri-firms' technological innovation employing fuzzy set qualitative comparative analysis (fsQCA). The study finds a well-designed set of ERI can promote technological innovation in agribusiness; control-command ERI cannot promote technological innovation in agribusiness solely, market-incentivized ERI is indispensable in promoting firms' innovation performance, implicit ERI plays an important role in promoting firms' innovation and voluntary ERI does not play a significant role in promoting firms' technological innovation. The government should coordinate among various types of ERI and improve the design of ERI to achieve a win-win situation for both economic and environmental performance in the agriculture sector. [ABSTRACT FROM AUTHOR]

Innovation is the first driving force to lead development, how to improve manufacturing innovation performance has become a hot topic. Based on 47 listed companies in the computer, communication and other electronic equipment manufacturing industry in the A-share market, this paper adopted the Fuzzy set qualitative comparative analysis (fsQCA) to explore the influencing factors of technology, organization and environment on the innovation performance of manufacturing industry and the improvement path. The findings are as follows: (1) A single condition is not a necessary condition for high innovation performance in manufacturing industry, but government support plays a key role in improving innovation performance in manufacturing industry. (2) There are two improvement paths for high innovation performance in manufacturing industry, which are specifically explained as "technology-environment dual improvement path" and "technology-organization-environment collaborative improvement path". (3) The improvement of innovation performance in the manufacturing industry is the result of multiple factors, showing the characteristics of "all paths lead to the same destination". Different manufacturing enterprises have different paths to improve innovation performance based on their actual conditions. Based on these findings, this study may provide some implications for the effective improvement of manufacturing innovation performance. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to propose an improved hesitation fuzzy multi-attribute decision-making method to realize green supply chain member selection under green innovation vision. The method uses hesitation fuzzy sets to express decision information of decision makers, takes green innovation capability as the evaluation perspective, and selects green innovation input, synergy of subjects in green supply chain, green innovation output capability, institutional innovation capability of enterprises in green supply chain, and green innovation sustainability as the indexes to evaluate the green innovation capability of enterprises. The multi-attribute decision method proposed in this paper takes into account the shortcomings of the original hesitant fuzzy multi-attribute decision method considering attribute weight optimization in the determination of attribute weights and scheme ranking, then proposes a three-point estimation method for scheme ranking and optimizes the attribute weights by quantifying the balance coefficients of the original decision method. Finally, an example is used to verify the rationality and effectiveness of the proposed method, and a comparison with the original method is made to highlight the advantages of this paper's method. This paper provides a certain theoretical basis for the selection of members in green supply chains, which helps the selection of members in green supply chains and provides some insight for similar hesitant fuzzy multi-attribute decision-making problems in other fields. In future research, the method proposed in this paper can be considered to combine with probabilistic hesitant fuzzy sets and some other fuzzy sets for method extensions to solve multi-attribute decision-making problems. [ABSTRACT FROM AUTHOR]

This paper adopts the fuzzy set qualitative comparative analysis method to carry out an empirical analysis on Chinese latecomer enterprises and examines the key factors and realization paths that affect the technology path transformation of latecomer enterprises. This paper finds that there are configuration characteristics among the influencing factors of the technological path transformation of latecomer enterprises. The paper reveals the causal complexity mechanism of multiple factors that jointly affect technology path transformation. The key factors that affect the technological path transformation of latecomer enterprises include organizational vigilance, strategic transformation capability, network connections breadth, resource governance depth, dynamics of the technological environment, and the scale of social demand for technology. The above factors not only emphasize that latecomer enterprises should focus on new technologies rather than the market but also reveal that strategic transformation capability and resource governance depth are the keys for enterprises to achieve technology path transformation. In addition, it is pointed out that latecomer enterprises should pay attention to the "window of opportunity" brought about by the scale of social demand for technology. The transition from technology path dependence to technology path transformation of latecomer enterprises is a process in which the key factor becomes stronger. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed braking intention identification control strategy has braking stability. As a widely-used construction machinery, the electric loader has the potential to recover braking energy due to its large mass and frequent starts and stops. Identifying braking intention accurately is the foundation of braking energy recovery. The typical braking condition of an electric loader is analyzed; the braking intention is divided into sliding brake, mild braking, moderate braking, and emergency braking. A large number of braking data were collected under different braking intentions, which are used as the basis for fuzzy control variable partitioning, fuzzy controller parameter setting and fuzzy control rule formulation. The control strategies of deceleration intention identification based on accelerator pedal, braking intention identification based on brake pedal and sliding brake intention identification are proposed in this paper, respectively. This paper takes the hydraulic brake pressure as a feedback parameter, even if there is hysteresis or failure based on the intention of pedal identification, the system can still provide sufficient braking strength to ensure the braking safety. The AMESim(R12)-Matlab/Simulink co-simulation model and prototype are built to verify the feasibility of the control strategy under different braking intention identification. The results show that the braking strength under stronger braking intention can satisfy the braking demand whether at a speed of 2 m/s or 12 m/s, which ensures the safety of emergency braking, and the electric loader can provide stable braking strength under different braking intention and different speed. This has good braking stability. [ABSTRACT FROM AUTHOR]

Circular intuitionistic fuzzy sets are further extensions of intuitionistic fuzzy sets with a stronger ability to express uncertain information than intuitionistic fuzzy sets. This paper firstly defines a new distance measure for circular intuitionistic fuzzy sets based on the theory of circular intuitionistic fuzzy sets, considering the information of four aspects: membership degree, non-membership degree, radius and the assignment of hesitation degree, and proves that the new distance satisfies the distance measure conditions. Secondly, by constructing a manual testing framework, the new distance is analyzed in comparison with the existing distance metric to show the rationality of the new method. Finally, the method is applied to fuzzy multi-criteria decision making to further demonstrate the effectiveness and practicality of the method. [ABSTRACT FROM AUTHOR]

Copyright of Serbian Journal of Management is the property of Serbian Journal of Management 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.)

The paper describes a novel online identification algorithm for a two-mass drive system. The multi-layer extended Kalman Filter (MKF) is proposed in the paper. The proposed estimator has two layers. In the first one, three single extended Kalman filters (EKF) are placed. In the second layer, based on the incoming signals from the first layer, the final states and parameters of the two-mass system are calculated. In the considered drive system, the stiffness coefficient of the elastic shaft and the time constant of the load machine is estimated. To improve the quality of estimated states, an additional system based on II types of fuzzy sets is proposed. The application of fuzzy MKF allows for a shorter identification time, as well as improves the accuracy of estimated parameters. The identified parameters of the two-mass system are used to calculate the coefficients of the implemented control structure. Theoretical considerations are supported by simulations and experimental tests. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and picking problem in storage systems with multiple blocks of two and three dimensions. The performance of these methods is compared using a set of well-known metrics and running an extensive battery of simulations based on a methodology widely used in the literature. The main contributions of this paper are (1) the hybridization of MOEAs to deal efficiently with the combination of orders in one or several picking tours, scheduling them for each picker, and (2) a multi-criteria approach to scheduling multiple picking teams for each wave of orders. Based on the experimental results obtained, it can be stated that, in environments with a large number of different items and orders with high variability in volume, the proposed approach can significantly reduce operating costs while allowing the decision-maker to anticipate the positioning of orders in the dispatch area. [ABSTRACT FROM AUTHOR]

This document is a special issue of the journal Nonlinear Studies, featuring interdisciplinary perspectives in applied mathematics. It includes articles on consumer behavior, diffusion of innovation, numerical methods, game theory, and optimization, covering domains such as engineering, management, and physics. The papers have undergone peer review and offer original and high-quality research. The document compiles research contributions on reliability analysis, mathematical modeling, differential equations, and optimization problems, with references for further exploration. The authors express gratitude to the contributors and reviewers for their valuable contributions. [Extracted from the article]

Many papers have been devoted to applying fuzzy sets to algebraic structures. In this paper, based on ideals, we investigate residuated lattices from fuzzy set theory, lattice theory, and coding theory points of view, and some applications of fuzzy sets in residuated lattices are presented. Since ideals are important concepts in the theory of algebraic structures used for formal fuzzy logic, first, we investigate the lattice of fuzzy ideals in residuated lattices and study some connections between fuzzy sets associated to ideals and Hadamard codes. Finally, we present applications of fuzzy sets in coding theory. [ABSTRACT FROM AUTHOR]

Spatial and temporal uncertainties are found in data for many critical applications. This paper describes the use of interval-based representations of some spatial and temporal information. Uncertainties in the information can arise from multiple sources in which degrees of support and non-support occur in evaluations. This motivates the use of intuitionistic fuzzy sets to permit the use of the positive and negative memberships to capture these uncertainties. The interval representations will include both simple and complex or nested intervals. The relationships between intervals such as overlapping, containing, etc. are then developed for both the simple and complex intervals. Such relationships are required to support the aggregation approaches of the interval information. Both averaging and merging approaches to interval aggregation are then developed. Furthermore, potential techniques for the associated aggregation of the interval intuitionistic fuzzy memberships are provided. A motivating example of maritime depth data required for safe navigation is used to illustrate the approach. Finally, some potential future developments are discussed. [ABSTRACT FROM AUTHOR]

Motivated by the fact that the fuzzy quasi-normed space provides a suitable framework for complexity analysis and has important roles in discussing some questions in theoretical computer science, this paper aims to study the nearest point problems in fuzzy quasi-normed spaces. First, by using the theory of dual space and the separation theorem of convex sets, the properties of the fuzzy distance from a point to a set in a fuzzy quasi-normed space are studied comprehensively. Second, more properties of the nearest point are given, and the existence, uniqueness, characterizations, and qualitative properties of the nearest points are obtained. The results obtained in this paper are of great significance for expanding the application fields of optimization theory. [ABSTRACT FROM AUTHOR]

This paper mainly studies and proves the roughness bound of disturbation fuzzy sets. Firstly, based on the theory of determining self-increment and uncertain self-decrement operators, the problem that the execution subsets are not equal sets is effectively solved, which hinders the quantitative study of disturbed fuzzy sets and lays a foundation for the quantitative study of the related properties of disturbed fuzzy sets in the future. The boundary of roughness measure of disturbing fuzzy set is further studied and proved. The new territories proposed in this paper can effectively avoid the unnecessary calculation space outside the boundary in the calculation process, so as to improve the work efficiency. [ABSTRACT FROM AUTHOR]

In the present paper, we introduce and discuss a new set of separation properties in fuzzy soft topological spaces called F S δ -separation and F S δ -regularity axioms by using fuzzy soft δ -open sets and the quasi-coincident relation. We provide a comprehensive study of their properties with some supporting examples. Our analysis includes more characterizations, results, and theorems related to these notions, which contributes to a deeper understanding of fuzzy soft separability properties. We show that the F S δ -separation and F S δ -regularity axioms are harmonic and heredity property. Additionally, we examine the connections between F S δ ∗ -compactness and F S δ -separation axioms and explore the relationships between them. Overall, this work offers a new perspective on the theory of separation properties in fuzzy soft topological spaces, as well as provides a robust foundation for further research in the transmission of properties from fuzzy soft topologies to fuzzy and soft topologies and vice-versa by swapping between the membership function and characteristic function in the case of fuzzy topology and the set of parameters and a singleton set in the case of soft topology. In the present paper, we introduce and discuss a new set of separation properties in fuzzy soft topological spaces called -separation and -regularity axioms by using fuzzy soft -open sets and the quasi-coincident relation. We provide a comprehensive study of their properties with some supporting examples. Our analysis includes more characterizations, results, and theorems related to these notions, which contributes to a deeper understanding of fuzzy soft separability properties. We show that the -separation and -regularity axioms are harmonic and heredity property. Additionally, we examine the connections between -compactness and -separation axioms and explore the relationships between them. Overall, this work offers a new perspective on the theory of separation properties in fuzzy soft topological spaces, as well as provides a robust foundation for further research in the transmission of properties from fuzzy soft topologies to fuzzy and soft topologies and vice-versa by swapping between the membership function and characteristic function in the case of fuzzy topology and the set of parameters and a singleton set in the case of soft topology. [ABSTRACT FROM AUTHOR]

This paper's aim is to extend and generalize the classic results regarding spectral radii and the corresponding resolvent sets for some different classes of bounded operators acting on fuzzy normed spaces. In this context, the fuzzy norm definition introduced giving shape to a new topology for a fuzzy space, namely a fuzzy topology, also gives the opportunity to study the behavior of various types of operators defined between fuzzy normed spaces, along with their spectral properties. There are several definitions for resolvent sets and consequently, several corresponding definitions of spectral radii that will be considered in this work, since these are non-equivalent ways of defining such notions. Spectral radii are calculated for a fuzzy Volterra type operator acting between fuzzy normed spaces. [ABSTRACT FROM AUTHOR]