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

Zuohua Miao; Hong Xu; Yong Chen; Xiangyang Zeng

doi:10.1117/12.813138

10 November 2008 An intelligent computational algorithm based on neural network for spatial data mining in adaptability evaluation

Zuohua Miao, Hong Xu, Yong Chen, Xiangyang Zeng

Author Affiliations +

Proceedings Volume 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses; 71461B (2008) https://doi.org/10.1117/12.813138
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

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.

Citation Download Citation

Zuohua Miao, Hong Xu, Yong Chen, and Xiangyang Zeng "An intelligent computational algorithm based on neural network for spatial data mining in adaptability evaluation", Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 71461B (10 November 2008); https://doi.org/10.1117/12.813138

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