神经网络方法在用水量预测中的应用

The Application of Neural Network Method in Water Quantity Predicting

采用自适应变步长的后向传播算法 (ABPM)构建了一个人工神经网络用水量预测模型。分别取一部分历史数据作为训练样本和测试样本 ,用训练样本对网络进行训练 ,然后用测试样本对模型进行评估。结果表明该模型收敛速度较快 ,预测精度高 ,为用水量预测提供了一种新的方法。

The following paper constructs a artificial neural network - named water quantity predicting model,using automatically adapting and step-self-changing back propagation method(ABPM).We take a part of the historical data from a tap water supplying enterprise as the training data and the other part as testing data.We train the network using the training data and then estimate the model using the testing data.The result of our experiment indicates that the model converges fast relatively and has a higher precision.The model proposes a new mothed for water quantity predicting.