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

Miao Zuohua, Xu Hong, Chen Yong, Zeng Xiangyang

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

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.

Original languageEnglish
Article number71461B
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume7146
DOIs
StatePublished - 2008
Externally publishedYes
EventGeoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses - Guangzhou, China
Duration: 28 Jun 200829 Jun 2008

Keywords

  • Adaptability evaluation
  • Back propagation
  • Intelligent compute
  • Spatial data mining

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