Piecewise Modeling Based on Particle Swarm Optimization Algorithm Using Numerical Data

We propose a piecewise modeling method using numerical data. The shape of the piecewise model is a rectangular form into a state-space. The vertex values of the rectangular regions are determined using particle swarm optimization because the optimal dividing solution is a nonlinear programming probl...

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Bibliographic Details
Published inIEEE International Fuzzy Systems conference proceedings pp. 1 - 6
Main Authors Taniguchi, Tadanari, Eciolaza, Luka
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 30.06.2024
Subjects
Computational modeling
Computer simulation
Data models
nonlinear system
Numerical models
Numerical simulation
particle swarm optimization
piecewise modeling
Programming
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ISSN1558-4739
DOI10.1109/FUZZ-IEEE60900.2024.10612184

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Summary:We propose a piecewise modeling method using numerical data. The shape of the piecewise model is a rectangular form into a state-space. The vertex values of the rectangular regions are determined using particle swarm optimization because the optimal dividing solution is a nonlinear programming problem. Using the particle swarm optimization as a multi-point search algorithm, the proposed method can determine optimal vertex values of the piecewise regions with minimal modeling errors. This paper considers some examples to demonstrate the effectiveness of the proposed method using numerical simulations.
ISSN:1558-4739
DOI:10.1109/FUZZ-IEEE60900.2024.10612184