摘要
将计算智能理论引入土地评价领域,构建了一个全新的土地适宜性评价模型。首先基于模糊逻辑和人工神经网络构造了一个模糊神经网络模型,然后采用改进的遗传算法进行训练,能够快速收敛到最优解,对初始的规则库进行修正,形成了一个自学习、自适应的评价系统。
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.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2005年第4期283-287,共5页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(40271088)
国家教育部留学回国人员基金资助项目(152174)
国家教育部跨世纪人才基金资助项目。
关键词
土地适宜性评价
计算智能
模糊神经网络
land suitability evaluation
computational intelligence
fuzzy neural networks