RBF神经网络在地下水动态预报中的应用  

Application of RBF Neural Network in the Prediction of Variation of Groundwater Level

作　　者：罗金鸣[1] 赵国材[1] 谷雨[1] 齐凯[1] 

机构地区：[1]辽宁工程技术大学,辽宁葫芦岛125105

出　　处：《电气技术》2008年第3期38-39,42,共3页Electrical Engineering

摘　　要：RBF(径向基函数)神经网络具有结构自适应确定、输出与初始权值无关的优良特性。通过Matlab仿真,此网络应用于某地的地下水动态模拟与预测,演示训练样本集与检测样本集的构建、原始数据的预处理、神经网络的构建训练、检测及结果评价的整个过程,取得了良好效果,并与BP网进行了对比,RBF网络是一种值得推广的地下水动态模拟与预测神经网络模型。RBF network has advan-tageous properties such as independence of the output on initial weight value and adaptation for determining the construction. Simulating in matlab,we apply the network for simulation and prediction of underground water dynamics of one place. And reach a good achievement in studying completly a whole process in the construction of training samples assemble and checking samples assemble,pretreatment of original data, establishment, training, inspection and result-evaluation of the neural network. In conclusion of BP network, RBF network is a neural network model on simulation and prediction of underground water dynamics which is deserved to be popula-rized.

关 键 词：地下水 动态模拟与预测 BP网络 RBF网络 

分 类 号：P641.8[天文地球—地质矿产勘探]