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Fuzzy decision function estimation using fuzzified particle swarm optimization
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DOI：10.1007/s13042-016-0561-8.png)
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Abstract
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Present paper reports an upgrade of particle swarm optimization (PSO) algorithm for fuzzy environment by the definition of the particles as fuzzy numbers and reformulating their motion by fuzzy equations. The proposed fuzzified PSO is used to construct a set of fuzzy hyperplanes in the feature space to distinguish different classes. Fuzzy decision hyperplane assign a fuzzy membership to each sample rather than allocating to a specific class. Also the weight vector of fuzzy decision hyperplane is a set of fuzzy numbers. The proposed fuzzy classifier is called fuzzified particle swarm classifier (FPS-classifier) and its performance is evaluated by some artificial and well known benchmarks data sets.
Keywords:
Fuzzified particle swarm classifier
Fuzzified particle swarm optimization
Fuzzy decision hyperplane
Heuristic classifiers
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