Topic
Fuzzy number
About: Fuzzy number is a research topic. Over the lifetime, 35606 publications have been published within this topic receiving 972544 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: A new method for the delay-dependent stability analysis and stabilization problems for continuous-time Takagi and Sugeno (T-S) fuzzy systems with a time-varying delay is suggested, which is less conservative than other existing ones.
Abstract: This paper is concerned with delay-dependent stability analysis and stabilization problems for continuous-time Takagi and Sugeno (T-S) fuzzy systems with a time-varying delay A new method for the delay-dependent stability analysis and stabilization is suggested, which is less conservative than other existing ones First, based on a fuzzy Lyapunov-Krasovskii functional (LKF), a delay-dependent stability criterion is derived for the open-loop fuzzy systems In the derivation process, some free fuzzy weighting matrices are introduced to express the relationships among the terms of the system equation, and among the terms in the Leibniz-Newton formula Then, a delay-dependent stabilization condition based on the so-called parallel distributed compensation (PDC) scheme is worked out for the closed-loop fuzzy systems The proposed stability criterion and stabilization condition are represented in terms of linear matrix inequalities (LMIs) and compared with the existing ones via two examples Finally, application to control of a truck-trailer is also given to illustrate the effectiveness of the proposed design method
244 citations
01 Jan 2002
TL;DR: This book discusses Granular Computing in Data Mining, Granular computing with Closeness and Negligibility Relations, and the application of Granularity Computing to Confirm Compliance with Non-Proliferation Treaty.
Abstract: 1: Granular Computing - A New Paradigm.- Some Reflections on Information Granulation and its Centrality in Granular Computing, Computing with Words, the Computational Theory of Perceptions and Precisiated Natural Language.- 2: Granular Computing in Data Mining.- Data Mining Using Granular Computing: Fast Algorithms for Finding Association Rules.- Knowledge Discovery with Words Using Cartesian Granule Features: An Analysis for Classification Problems.- Validation of Concept Representation with Rule Induction and Linguistic Variables.- Granular Computing Using Information Tables.- A Query-Driven Interesting Rule Discovery Using Association and Spanning Operations.- 3: Data Mining.- An Interactive Visualization System for Mining Association Rules.- Algorithms for Mining System Audit Data.- Scoring and Ranking the Data Using Association Rules.- Finding Unexpected Patterns in Data.- Discovery of Approximate Knowledge in Medical Databases Based on Rough Set Model.- 4: Granular Computing.- Observability and the Case of Probability.- Granulation and Granularity via Conceptual Structures: A Perspective From the Point of View of Fuzzy Concept Lattices.- Granular Computing with Closeness and Negligibility Relations.- Application of Granularity Computing to Confirm Compliance with Non-Proliferation Treaty.- Basic Issues of Computing with Granular Probabilities.- Multi-dimensional Aggregation of Fuzzy Numbers Through the Extension Principle.- On Optimal Fuzzy Information Granulation.- Ordinal Decision Making with a Notion of Acceptable: Denoted Ordinal Scales.- A Framework for Building Intelligent Information-Processing Systems Based on Granular Factor Space.- 5: Rough Sets and Granular Computing.- GRS: A Generalized Rough Sets Model.- Structure of Upper and Lower Approximation Spaces of Infinite Sets.- Indexed Rough Approximations, A Polymodal System, and Generalized Possibility Measures.- Granularity, Multi-valued Logic, Bayes' Theorem and Rough Sets.- The Generic Rough Set Inductive Logic Programming (gRS-ILP) Model.- Possibilistic Data Analysis and Its Similarity to Rough Sets.
244 citations
26 Jun 1994
TL;DR: A new version of ID3 algorithm is proposed to generate an understandable fuzzy decision tree using fuzzy sets defined by a user to be applied to diagnosis for potential transformers by analyzing gas in oil.
Abstract: A popular and particularly efficient method for making a decision tree for classification from symbolic data is ID3 algorithm. Revised algorithms for numerical data have been proposed, some of which divide a numerical range into several intervals or fuzzy intervals. Their decision trees, however, are not easy to understand. We propose a new version of ID3 algorithm to generate an understandable fuzzy decision tree using fuzzy sets defined by a user. We apply it to diagnosis for potential transformers by analyzing gas in oil. >
244 citations
01 Dec 1987
TL;DR: A unified approach for comparing the performance of fuzzy and nonfuzzy controller designs is presented and relationships are established between the gain parameters for the two classes of controller designs.
Abstract: A unified approach for comparing the performance of fuzzy and nonfuzzy controller designs is presented. Relationships are established between the gain parameters for the two classes of controller designs. The methods presented apply equally well to proportional-plus-integral, linear multiband, and multilevel relay controllers.
243 citations
TL;DR: It is observed that it is possible to have degrees of compactness, which is called α-compactness (α a member of a designated lattice), and a Tychonoff Theorem is obtained for an arbitrary product of α-Compact fuzzy spaces and a 1-point compactification.
242 citations