Environmental selection using a fuzzy classifier for multiobjective evolutionary algorithms. The quality of solutions in multiobjective evolutionary algorithms (MOEAs) is usually evaluated by objective functions. However, function evaluations (FEs) are usually time-consuming in real-world problems.
Jun 26, 2021 · In this paper, we propose a fuzzy classifier-based selection strategy to reduce the number of FEs of MOEAs.
Jul 14, 2021 · In this paper, we proposed a fuzzy classifier-based selection (FCS) strategy for multiobjective evolutionary algorithms (MOEAs) to re- duce ...
In this work, we propose a fuzzy rule-based system to predict energy comsumption of a kind of Evolutionary Algorithm, Genetic Prohramming, given the device in ...
We propose a classification-assisted environmental selection (CAES) strategy in this paper to decrease the number of function evaluations in MOEAs.
MultiObjectiveEvolutionaryFuzzyClassifier constructs a fuzzy rule based classifier by using the ENORA Multi-objective Evolutionary Algorithm.
Missing: Environmental | Show results with:Environmental
This paper proposes a fuzzy classification-assisted environmental selection (FAES) scheme to reduce the number of objective evaluations of MOEAs. The proposed ...
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This paper proposes the evolutionary algorithm MeEA of multi-ecological environment selection strategy and uses this algorithm to solve MaOPs.
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Mar 18, 2019 · A fast and scalable multiobjective genetic fuzzy system for linguistic fuzzy modeling in high-dimensional regression problems. IEEE Transaction ...
In this work, we propose a novel multivariate feature selection method in which both search strategy and classifier are based on multi-objective evolutionary ...
Missing: Environmental | Show results with:Environmental