计算机与数字工程2012，Vol.40Issue(10)：40-42,50,4.
基于BP神经网络的矿山地下水位预测研究
Study of Prediction of Mining Groundwater Level Based on BP Neural Network
卓中文 1王山东 1杨松1
作者信息
- 1. 河海大学地球科学与工程学院 南京 210098
- 折叠
摘要
Abstract
The model of the prediction of mine groundwater level is set up adopt the BP neural network technology, use the three factors of the rainfall, displacement and pre—water level of the mining area as the input layer, as well as use mining groundwater level as the output layer. This paper describes the basic algorithm of how to use BP neural network realize prediction of mining groundwater level, the measured water level of the long—term observation wells in the mine of the study area as the experimental data and to make the error analysis. The final outcome can be achieved the purpose of predict mining groundwater level, and provides a strong basis to analyze the trend of groundwater depression cone.关键词
BP神经网络/地下水位预测/数据归一化Key words
BP neural network/ prediction of groundwater level/ data normalization分类
信息技术与安全科学引用本文复制引用
卓中文,王山东,杨松..基于BP神经网络的矿山地下水位预测研究[J].计算机与数字工程,2012,40(10):40-42,50,4.
