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 |
| 卷 | 7146 |
| DOI | |
| 出版状态 | 已出版 - 2008 |
| 已对外发布 | 是 |
| 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 2008 → 29 6月 2008 |
指纹
探究 'An intelligent computational algorithm based on neural network for spatial data mining in adaptability evaluation' 的科研主题。它们共同构成独一无二的指纹。引用此
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver