Title :
Stabilization Analysis of Side-slope Based on Self-organizing Feature Map Neural Net
Author :
Li, Ying ; Qie, Zhihong ; Wu, Xinmiao ; Zhang, Zhiyu
Author_Institution :
Dept. of water conservancy Eng., Hebei Agric. Univ., Baoding
Abstract :
Self-organizing feature map (SOFM) was applied to analyze the stabilization of side-slope. A SOFM network model, which was trained and tested by the engineering examples, was established. The research shows that the SOFM presents excellent network performance, high prediction precision and is easy to run. As a result, the method is an effective way to evaluate the state of side-slope
Keywords :
civil engineering computing; learning (artificial intelligence); mechanical stability; self-organising feature maps; SOFM network model; network performance; prediction precision; self-organizing feature map neural net; side-slope stabilization analysis; side-slope state evaluation; Agricultural engineering; Agriculture; Artificial neural networks; Biological neural networks; Biological system modeling; History; Neural networks; Neurons; Pattern recognition; Water conservation; Evaluation; Self-organizing Feature Map (SOFM); Side-slope; Stabilization;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.249
