Improved Type2-NPCM Fuzzy Clustering Algorithm Based on Adaptive Particle Swarm Optimization for Takagi–Sugeno Fuzzy Modeling Identification
In this paper, an improved Type2-NPCM clustering algorithm based on improved adaptive particle swarm optimization called Type2-NPCM-IAPSO is proposed. First, a new clustering algorithm called Type2-NPCM is proposed. The Type2-NPCM algorithm can solve the problems encountered by the algorithms FCM, G...
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| Vydáno v: | International journal of fuzzy systems Ročník 22; číslo 6; s. 2011 - 2024 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.09.2020
Springer Nature B.V |
| Témata: | |
| ISSN: | 1562-2479, 2199-3211 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | In this paper, an improved Type2-NPCM clustering algorithm based on improved adaptive particle swarm optimization called Type2-NPCM-IAPSO is proposed. First, a new clustering algorithm called Type2-NPCM is proposed. The Type2-NPCM algorithm can solve the problems encountered by the algorithms FCM, G-K, PCM and NPCM (sensitivity to noise or aberrant points and local minimal sensitivity), etc. Second, we combined our Type2-NPCM algorithm with the improved adaptive particle swarm optimization IAPSO algorithm to ensure proper convergence to a local minimum of the objective function. The effectiveness of the proposed Type2-NPCM-IAPSO algorithm was tested on the electro-hydraulic system, convection system and other nonlinear systems described by differential equation. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1562-2479 2199-3211 |
| DOI: | 10.1007/s40815-020-00881-2 |