Improving the accuracy while preserving the interpretability of fuzzy function approximators by means of multi-objective evolutionary algorithms

DOI10.1016/j.ijar.2006.02.006zbMath1109.68090OpenAlexW1982701576MaRDI QIDQ868121

Fernando Rojas, Jesús González, Luis J. Herrera, Alberto Guillén, Héctor Pomares, José M. Palomares, Ignacio Rojas

Publication date: 19 February 2007

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2006.02.006

zbMATH Keywords

multi-objective optimization evolutionary algorithms fuzzy systems function approximation

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

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Cites Work

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