An improved fuzzy ARTMAP network and its application in wetland classification

This work mainly discusses the application of an improved fuzzy ARTMAP network based on fuzzy logic in wetland classification. The main improvement is represented in two phases: first in the category competition phase, fuzzy reasoning replaces the simply similarity criterion; second in studying (resonance) phase, not only the winning neuron´s weights but also the fuzzy membership functions are updated according to input characters. The data source is TM images of Zhalong wetland nature reserve in north China, and both spectrum and spatial characters are extracted from it. A comparison of classification performance of three automatic classifiers, namely the improved fuzzy ARTMAP, the normal fuzzy ARTMAP and BPNN, is made in This work. The result indicates that the improved fuzzy ARTMAP is superior to other classifiers in supervised classification of wetland.