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An intelligent computational algorithm based on neural network for spatial data mining in adaptability evaluation

科研成果: 期刊稿件会议文章同行评审

1 引用 (Scopus)

摘要

Back-propagation neural network model (BPNN) is an intelligent computational model based on stylebook learning. This model is different from traditional adaptability symbolic logic reasoning method based on knowledge and rules. At the same time, BPNN model has shortcoming such as: slowly convergence speed and partial minimum. During the process of adaptability evaluation, the factors were diverse, complicated and uncertain, so an effectual model should adopt the technique of data mining method and fuzzy logical technology. In this paper, the author ameliorated the backpropagation of BPNN and applied fuzzy logical theory for dynamic inference of fuzzy rules. Authors also give detail description on training and experiment process of the novel model.

源语言英语
文章编号71461B
期刊Proceedings of SPIE - The International Society for Optical Engineering
7146
DOI
出版状态已出版 - 2008
已对外发布
活动Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses - Guangzhou, 中国
期限: 28 6月 200829 6月 2008

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