| 基于计算智能的土地适宜性评价模型 |
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| 引用本文： | 刘耀林,焦利民.基于计算智能的土地适宜性评价模型[J].武汉大学学报(信息科学版),2005,30(4):283-287. |
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| 作者姓名： | 刘耀林 焦利民 |
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| 作者单位： | 武汉大学资源与环境科学学院,武汉市珞喻路129号,430079;武汉大学教育部地理信息系统重点实验室,武汉市珞喻路129号,430079 |
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| 基金项目： | 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。 |
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| 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。
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| 关 键 词： | 土地适宜性评价 计算智能 模糊神经网络 |
| 文章编号： | 1671-8860(2005)04-0283-05 |
| 修稿时间： | 2005年2月7日 |
Model of Land Suitability Evaluation Based on Computational Intelligence |
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| LIU Yaolin,JIAO Limin.Model of Land Suitability Evaluation Based on Computational Intelligence[J].Geomatics and Information Science of Wuhan University,2005,30(4):283-287. |
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| Authors: | LIU Yaolin JIAO Limin |
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| Institution: | LIU Yaolin 1,2 JIAO Limin 1,2 |
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| 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. |
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| Keywords: | land suitability evaluation computational intelligence fuzzy neural networks |
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