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Genetic Algorithm Optimization for Type-2 Non-singleton Fuzzy Logic Controllers Read chapter Read first chapter

2014 | OriginalPaper | Chapter

A Comparative Study of Membership Functions for an Interval Type-2 Fuzzy System used to Dynamic Parameter Adaptation in Particle Swarm Optimization

Authors : Frumen Olivas, Fevrier Valdez, Oscar Castillo

Published in: Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Publisher: Springer International Publishing

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Abstract

This chapter present an analysis of the effects in quality results that brings the different types of membership functions in an interval type-2 fuzzy system used to adapt some parameters of Particle Swarm Optimization (PSO). Benchmark mathematical functions are used to test the methods and a comparison is performed.

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previous chapter Neural Network with Fuzzy Weights Using Type-1 and Type-2 Fuzzy Learning with Gaussian Membership Functions
next chapter Genetic Optimization of Type-2 Fuzzy Integrators in Ensembles of ANFIS Models for Time Series Prediction
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Metadata
Title
A Comparative Study of Membership Functions for an Interval Type-2 Fuzzy System used to Dynamic Parameter Adaptation in Particle Swarm Optimization
Authors
Frumen Olivas
Fevrier Valdez
Oscar Castillo
Copyright Year
2014
Book
Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Print ISBN: 978-3-319-05169-7

Electronic ISBN: 978-3-319-05170-3

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-05170-3_5

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