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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Veröffentlicht in:	International journal of fuzzy systems Jg. 22; H. 6; S. 2011 - 2024
Hauptverfasser:	Houcine, Lassad, Bouzbida, Mohamed, Chaari, Abdelkader
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020 Springer Nature B.V
Schlagworte:	Adaptive algorithms Artificial Intelligence Clustering Computational Intelligence Differential equations Engineering Fuzzy sets Heuristic Hydraulic equipment Identification Management Science Memberships Methods Noise sensitivity Nonlinear systems Operations Research Optimization algorithms Particle swarm optimization Type2-NPCM clustering algorithm Takagi–Sugeno fuzzy modeling Improved adaptive particle swarm optimization (IAPSO) Fuzzy clustering Type2-NPCM-IAPSO algorithm NPCM algorithm
ISSN:	1562-2479, 2199-3211
Online-Zugang:	Volltext
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