Application of neural network to identify the remote sensing data of hillslide

Ting Shiuan Wang, Ting-To Yu

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

This study presents the results of neural network simulation of hillside area prediction from remote sensing data. Five neural network methods were compared, which were Back Propagation Network (BPN), Extend Neuron Networks (ENN), Fuzzy Neural Network (FNN), Analysis Adjustment Synthesis Network (AASN), and Genetic Algorithm Neural Network (GANN). Three factors were used as the predictor in this study, which were NDVI value, shape factor, and color difference. The result reveals that the BPN is the best choice, because the error is the lowest among the five schemes in this study.

原文English
主出版物標題Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
頁面661-665
頁數5
DOIs
出版狀態Published - 2011 十一月 7
事件2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 - Guilin, Guangxi, China
持續時間: 2011 七月 102011 七月 13

出版系列

名字Proceedings - International Conference on Machine Learning and Cybernetics
2
ISSN(列印)2160-133X
ISSN(電子)2160-1348

Other

Other2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
國家/地區China
城市Guilin, Guangxi
期間11-07-1011-07-13

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 計算機理論與數學
  • 電腦網路與通信
  • 人機介面

指紋

深入研究「Application of neural network to identify the remote sensing data of hillslide」主題。共同形成了獨特的指紋。

引用此