煤矿安全2012，Vol.43Issue(3)：117-120,4.
AGO-BP神经网络在主要影响角正切求取中的应用
Application of AGO - BP Neural Network to the Tangent Calculation Method of the Main Influencing Angle
吴朝阳 1李宁1
作者信息
- 1. 中国矿业大学资源与地球科学学院,江苏徐州221008
- 折叠
摘要
Abstract
The tangent of the main influencing angle tanβ is one of the most important parameter for mining subsidence prediction with the probability integral method and it determines the range of surface subsidence. Based on analyzing the geologic and mining factors which affect the tangent of the main influencing angle, the paper constructed an AGO - BP neutral network model. This model prepro- cessed the selected original data on the basis of grey theory, and then calculated the tangent of the main influencing angle with BP neu- ral network model. The AGO -BP neural network model not only can adjust the network parameters automatically, but also can avoid the instability problem compared with only using BP neural network model. The tangent of the main influencing angle prediction is more accuracy with the AGO -BP neural network model.关键词
主要影响角正切/BP神经网络/数据累加/地表沉陷Key words
tangent of the main influencing angle/BP neutral network/data accmnulation/surface subsidence分类
矿业与冶金引用本文复制引用
吴朝阳,李宁..AGO-BP神经网络在主要影响角正切求取中的应用[J].煤矿安全,2012,43(3):117-120,4.
