Author
Zhenyuan Wang
Other affiliations: Binghamton University, The Chinese University of Hong Kong, Hebei University
Bio: Zhenyuan Wang is an academic researcher from University of Nebraska Omaha. The author has contributed to research in topics: Fuzzy measure theory & Choquet integral. The author has an hindex of 26, co-authored 102 publications receiving 3541 citations. Previous affiliations of Zhenyuan Wang include Binghamton University & The Chinese University of Hong Kong.
Papers published on a yearly basis
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Book•
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31 Jan 1993
TL;DR: Introduction.
Abstract: Introduction. Required Background in Set Theory. Fuzzy Measures. Extensions. Structural Characteristics for Set Functions. Measurable Functions on Fuzzy Measure Spaces. Fuzzy Integrals. PanIntegrals. Applications. Index.
1,187 citations
Book•
27 Oct 2008
TL;DR: This chapter discusses the development of Structural Characteristics for Set Functions and Measurable Functions on Monotone Measure Spaces in the context of Generalized Measure Theory.
Abstract: Preliminaries.- Basic Ideas of Generalized Measure Theory.- Special Areas of Generalized Measure Theory.- Extensions.- Structural Characteristics for Set Functions.- Measurable Functions on Monotone Measure Spaces.- Integration.- Sugeno Integrals.- Pan-Integrals.- Choquet Integrals.- Upper and Lower Integrals.- Constructing General Measures.- Fuzzification of Generalized Measures and the Choquet Integral.- Applications of Generalized Measure Theory.
453 citations
TL;DR: Some convergence theorems of sequence of fuzzy integrals are proved, especially, using the concept of autocontinuity, a necessary and sufficient condition for the convergence in measure theorem is given.
159 citations
TL;DR: A specially designed genetic algorithm is employed to realize the optimization in determining the nonadditive set function from given input-output data when the nonlinear integral is viewed as a multi-input single-output system.
123 citations
TL;DR: An efficient genetic algorithm for constructing a suitable fuzzy measure from relevant input-output data is described, which has a broad applicability in various problem areas, such as decision making, cluster analysis, pattern recognition, image and speech processing, and expert systems.
Abstract: A synthetic evaluation of a given object in terms of multiple factors that contribute to some feature of the object (quality, performance, etc) may be regarded as a system with multiple inputs and one output Traditionally, the output is expressed as the weighted average of the inputs Unfortunately, this method is severely limited as it cannot capture any inherent relation among the factors involved This limitation can be overcome by using the Choquet integral or the fuzzy integral with respect to a fuzzy measure that captures the relation among the factors The crux of this method is to determine the right fuzzy measure In this paper, we describe an efficient genetic algorithm for constructing a suitable fuzzy measure from relevant input-output data This algorithm has a broad applicability in various problem areas, such as decision making, cluster analysis, pattern recognition, image and speech processing, and expert systems
113 citations
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01 Jan 2007
TL;DR: A broad introduction into the topic of aggregation functions, and provides a concise account of the properties and the main classes of such functions, including classical means, medians, ordered weighted averaging functions, Choquet and Sugeno integrals, triangular norms, conorms and copulas, uninorms, nullnorms, and symmetric sums.
Abstract: Aggregation of information is of primary importance in the construction of knowledge based systems in various domains, ranging from medicine, economics, and engineering to decision-making processes, artificial intelligence, robotics, and machine learning. This book gives a broad introduction into the topic of aggregation functions, and provides a concise account of the properties and the main classes of such functions, including classical means, medians, ordered weighted averaging functions, Choquet and Sugeno integrals, triangular norms, conorms and copulas, uninorms, nullnorms, and symmetric sums. It also presents some state-of-the-art techniques, many graphical illustrations and new interpolatory aggregation functions. A particular attention is paid to identification and construction of aggregation functions from application specific requirements and empirical data. This book provides scientists, IT specialists and system architects with a self-contained easy-to-use guide, as well as examples of computer code and a software package. It will facilitate construction of decision support, expert, recommender, control and many other intelligent systems.
1,445 citations
TL;DR: In this paper, fuzzy logic is viewed in a nonstandard perspective and the cornerstones of fuzzy logic-and its principal distinguishing features-are: graduation, granulation, precisiation and the concept of a generalized constraint.
1,253 citations