Abstract
A novel model of land suitability evaluation is built based on computational intelligence (CI). A fuzzy neural network (FNN) is constructed by the integration of fuzzy logic and artificial neural network (ANN). The structure and process of this network is clear. Fuzzy rules (knowledge) are expressed in the model explicitly, and can be self-adjusted by learning from samples. Genetic algorithm (GA) is employed as the learning algorithm to train the network, and makes the training of the model efficient. This model is a self-learning and self-adaptive system with a rule set revised by training.
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Funded by the Open Research Fund Program of GIS Laboratory of Wuhan University (No. wd200609).
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Jiao, L., Liu, Y. Model of land suitability evaluation based on computational intelligence. Geo-spat. Inf. Sc. 10, 151–156 (2007). https://doi.org/10.1007/s11806-007-0053-9
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DOI: https://doi.org/10.1007/s11806-007-0053-9