We present a method by using the hierarchical cluster-based Multispecies particle swarm optimization to generate a fuzzy system\r\nof Takagi-Sugeno-Kang type encapsulated in a geographical information system considered as environmental decision support\r\nfor spatial analysis. We consider a spatial area partitioned in subzones: the data measured in each subzone are used to extract a\r\nfuzzy rule set of above mentioned type.We adopt a similarity index (greater than a specific threshold) for comparing fuzzy systems\r\ngenerated for adjacent subzones.
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