Journal ArticleDOI
A new method for constructing membership functions and fuzzy rules from training examples
Tzu-Ping Wu,Shyi-Ming Chen +1 more
- Vol. 29, Iss: 1, pp 25-40
TLDR
A new fuzzy learning algorithm based on thealpha-cuts of equivalence relations and the alpha-cutting of fuzzy sets to construct the membership functions of the input variables and the output variables of fuzzy rules and to induce the fuzzy rules from the numerical training data set is proposed.Abstract:
To extract knowledge from a set of numerical data and build up a rule-based system is an important research topic in knowledge acquisition and expert systems. In recent years, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed. In this paper, we propose a new fuzzy learning algorithm based on the /spl alpha/-cuts of equivalence relations and the /spl alpha/-cuts of fuzzy sets to construct the membership functions of the input variables and the output variables of fuzzy rules and to induce the fuzzy rules from the numerical training data set. Based on the proposed fuzzy learning algorithm, we also implemented a program on a Pentium PC using the MATLAB development tool to deal with the Iris data classification problem. The experimental results show that the proposed fuzzy learning algorithm has a higher average classification ratio and can generate fewer rules than the existing algorithm.read more
Citations
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Journal ArticleDOI
Expert system methodologies and applications—a decade review from 1995 to 2004
TL;DR: This paper surveys expert systems (ES) development using a literature review and classification of articles from 1995 to 2004 with a keyword index and article abstract in order to explore how ES methodologies and applications have developed during this period.
Journal ArticleDOI
Self-adaptive neuro-fuzzy inference systems for classification applications
Jeen-Shing Wang,C.S.G. Lee +1 more
TL;DR: This paper presents a self- Adaptive neuro-fuzzy inference system (SANFIS) that is capable of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base for interpreting the embedded knowledge of a system from the given training data set.
Journal ArticleDOI
A neuro fuzzy expert system for heart disease diagnosis
TL;DR: The neuro fuzzy classification of the disease with the help of genetic algorithms for feature selection is the frame work of the proposed system.
Journal ArticleDOI
Training fuzzy systems with the extended Kalman filter
TL;DR: It is demonstrated that the Kalman filter can be an effective tool for improving the performance of a fuzzy system and is compared with gradient descent and adaptive neuro-fuzzy inference system (ANFIS) based optimization of fuzzy membership functions.
Journal ArticleDOI
Automatic Design of Hierarchical Takagi–Sugeno Type Fuzzy Systems Using Evolutionary Algorithms
TL;DR: This paper presents an automatic way of evolving hierarchical Takagi-Sugeno fuzzy systems (TS-FS) using probabilistic incremental program evolution (PIPE) with specific instructions and fine tuning of the if - then rule's parameters encoded in the structure using evolutionary programming (EP).
References
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Journal ArticleDOI
Fuzzy identification of systems and its applications to modeling and control
T. Takagi,Michio Sugeno +1 more
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
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The concept of a linguistic variable and its application to approximate reasoning—II☆
TL;DR: Much of what constitutes the core of scientific knowledge may be regarded as a reservoir of concepts and techniques which can be drawn upon to construct mathematical models of various types of systems and thereby yield quantitative information concerning their behavior.