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961 results on '"Son, Le Hoang"'

12. Enhancement of Voting Scores with Multiple Attributes Based on VoteRank++ to Identify Influential Nodes in Social Networks

Author

Van Duong, Pham, Dang, Tuan Minh, Son, Le Hoang, Van Hai, Pham, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Pinto, Adilson Luiz, editor, and Arencibia-Jorge, Ricardo, editor

Published
2022
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13. Enhancement of Gravity Centrality Measure Based on Local Clustering Method by Identifying Influential Nodes in Social Networks

Author

Van Duong, Pham, Dinh, Xuan Truong, Son, Le Hoang, Van Hai, Pham, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Wang, Shui-Hua, editor, and Zhang, Yu-Dong, editor

Published
2022
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19. Attribute Reduction on Decision Tables Based on Hausdorff Topology.

Author

Giang, Nguyen Long, Dai, Tran Thanh, Son, Le Hoang, Ngan, Tran Thi, Son, Nguyen Nhu, and Giap, Cu Nguyen

Abstract

Attribute reduction through the combined approach of Rough Sets (RS) and algebraic topology is an open research topic with significant potential for applications. Several research works have introduced a strong relationship between RS and topology spaces for the attribute reduction problem. However, the mentioned recent methods followed a strategy to construct a new measure for attribute selection. Meanwhile, the strategy for searching for the reduct is still to select each attribute and gradually add it to the reduct. Consequently, those methods tended to be inefficient for high-dimensional datasets. To overcome these challenges, we use the separability property of Hausdorff topology to quickly identify distinguishable attributes, this approach significantly reduces the time for the attribute filtering stage of the algorithm. In addition, we propose the concept of Hausdorff topological homomorphism to construct candidate reducts, this method significantly reduces the number of candidate reducts for the wrapper stage of the algorithm. These are the two main stages that have the most effect on reducing computing time for the attribute reduction of the proposed algorithm, which we call the Cluster Filter Wrapper algorithm based on Hausdorff Topology. Experimental validation on the UCI Machine Learning Repository Data shows that the proposed method achieves efficiency in both the execution time and the size of the reduct. [ABSTRACT FROM AUTHOR]

Published
2024
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20. A New Decision Making Model Based on Complex Intuitionistic Fuzzy Soft Lattice for Traffic Monitoring in the Pandemic Scenarios.

Author

Quek, Shio Gai, Selvachandran, Ganeshsree, Jayakumar, Vimala, Duong, Phet, and Son, Le Hoang

Abstract

Various representations of real‐life scenarios by algebraic structures are of vital importance in the modern era of Industrial Revolution 4.0 as it enables such data to be interpreted and processed by artificial intelligence, thus bridging the interaction gap between humans and machines. In response to that, this article proposes a new decision making model for traffic control among shopping complexes utilizing the novel concept of the complex intuitionistic fuzzy soft lattice of the circular type (CIFSL‐C), which takes the time within a day as truly directional entities. As a result, CIFSL‐C possesses the combined structural complexity and the level of sophistication of all the previous algebraic models which they are derived from, enabling them to be utilized in representing many real‐life scenarios, including those related to the pandemic, which will be rigorously discussed in this article. In addition, the complex intuitionistic fuzzy soft lattice of the quaternion type (CIFSL‐Q) will also be established. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Colorectal Cancer Diagnosis with Complex Fuzzy Inference System

Author

Ngan, Tran Thi, Lan, Luong Thi Hong, Tuan, Tran Manh, Son, Le Hoang, Tuan, Le Minh, Minh, Nguyen Hai, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Satapathy, Suresh Chandra, editor, Bhateja, Vikrant, editor, Nguyen, Bao Le, editor, Nguyen, Nhu Gia, editor, and Le, Dac-Nhuong, editor

Published
2020
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26. A Proposal of Expert System Using Deep Learning Neural Networks and Fuzzy Rules for Diagnosing Heart Disease

Author

Van Pham, Hai, Son, Le Hoang, Tuan, Le Minh, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Satapathy, Suresh Chandra, editor, Bhateja, Vikrant, editor, Nguyen, Bao Le, editor, Nguyen, Nhu Gia, editor, and Le, Dac-Nhuong, editor

Published
2020
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28. A Neutrosophic Recommender System for Medical Diagnosis Based on Algebraic Neutrosophic Measures

Author

Ali, Mumtaz, Van Minh, Nguyen, and Son, Le Hoang

Subjects
Computer Science - Artificial Intelligence
Abstract

Neutrosophic set has the ability to handle uncertain, incomplete, inconsistent, indeterminate information in a more accurate way. In this paper, we proposed a neutrosophic recommender system to predict the diseases based on neutrosophic set which includes single-criterion neutrosophic recommender system (SC-NRS) and multi-criterion neutrosophic recommender system (MC-NRS). Further, we investigated some algebraic operations of neutrosophic recommender system such as union, complement, intersection, probabilistic sum, bold sum, bold intersection, bounded difference, symmetric difference, convex linear sum of min and max operators, Cartesian product, associativity, commutativity and distributive. Based on these operations, we studied the algebraic structures such as lattices, Kleen algebra, de Morgan algebra, Brouwerian algebra, BCK algebra, Stone algebra and MV algebra. In addition, we introduced several types of similarity measures based on these algebraic operations and studied some of their theoretic properties. Moreover, we accomplished a prediction formula using the proposed algebraic similarity measure. We also proposed a new algorithm for medical diagnosis based on neutrosophic recommender system. Finally to check the validity of the proposed methodology, we made experiments on the datasets Heart, RHC, Breast cancer, Diabetes and DMD. At the end, we presented the MSE and computational time by comparing the proposed algorithm with the relevant ones such as ICSM, DSM, CARE, CFMD, as well as other variants namely Variant 67, Variant 69, and Varian 71 both in tabular and graphical form to analyze the efficiency and accuracy. Finally we analyzed the strength of all 8 algorithms by ANOVA statistical tool., Comment: Keywords: Medical diagnosis, neutrosophic set, neutrosophic recommender system, non-linear regression model

Published
2016

32. Fuzzy approaches to context variable in fuzzy geographically weighted clustering

Author

Van Minh, Nguyen and Son, Le Hoang

Subjects
Computer Science - Artificial Intelligence, 62H30, I.5.3
Abstract

Fuzzy Geographically Weighted Clustering (FGWC) is considered as a suitable tool for the analysis of geo-demographic data that assists the provision and planning of products and services to local people. Context variables were attached to FGWC in order to accelerate the computing speed of the algorithm and to focus the results on the domain of interests. Nonetheless, the determination of exact, crisp values of the context variable is a hard task. In this paper, we propose two novel methods using fuzzy approaches for that determination. A numerical example is given to illustrate the uses of the proposed methods., Comment: 11 pages

Published
2015
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