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基于MATLAB BP神经网络的岩溶渗漏污染预测一例
引用本文:綦娅,陈兴帅,褚学伟. 基于MATLAB BP神经网络的岩溶渗漏污染预测一例[J]. 工程勘察, 2010, 0(10): 41-45,56
作者姓名:綦娅  陈兴帅  褚学伟
作者单位:[1]贵州大学资源与环境工程学院,贵阳550003 [2]贵州大学矿业学院,贵阳550003
摘    要:本文以摆纪磷石膏堆场为研究对象,采用了地下水物质迁移模型中的"黑箱"模型,即运用MATLAB的BP神经网络建立磷石膏堆场岩溶渗漏污染预测模型,实现了人工神经网络对堆场岩溶渗漏污染的预测。在岩溶渗漏管道为单一管道类型时,模型预测值基本与实测值吻合,误差较小,效果较为理想。但对复杂的岩溶渗漏管道类型,虽然能大致反映出污染物浓度变化的趋势,但模型精度不够,误差较大,因此还需进一步收集数据进行模型的优化,使其达到理想的预测效果。

关 键 词:岩溶  渗漏污染预测  MATLAB  BP神经网络

Prediction of pollution of karst leakage in Baiji ardealite site with BP neural network system
Qi Ya,Cheng Xingshuai,Chu Xuewei. Prediction of pollution of karst leakage in Baiji ardealite site with BP neural network system[J]. Geotechnical Investigation & Surveying, 2010, 0(10): 41-45,56
Authors:Qi Ya  Cheng Xingshuai  Chu Xuewei
Affiliation:1. College of Resources and Environmental Engineering, Guizhou University, Guizhou 550003, China; 2. Mining college of Guizhou University, Guizhou 550003, China)
Abstract:Karst groundwater pollution problems in Guizhou province are getting more and more prominent. It has become a threat to the groundwater resources of Karst area. Based on evaluating and analyzing the karst groundwater leakage of the slag yard, a model of predicting the Krast groundwater seepage with BP neural network system with NNTOOL of neural network tool box in MATLAB is established and the feasibility of the BP neural networks model in karst groundwater is realized. The predicted value compares well with the measured value based on the Krast groundwater seepage with the type of single channel of small error. Although the model represents the trend of the change with pollutant concentration, the precision is inadequate. Therefore, it needs to reach the ideal prediction with more data.
Keywords:Krast  the prediction of groundwater leakage  MATLAB  BP neural network
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