人工鱼群神经网络应用于城市污水处理厂进水量预测研究

城市污水处理厂进水量的预测精度对污水厂的安全运行与科学管理具有重要影响。将人工鱼群算法用于神经网络的训练过程，并根据污水厂进水量的变化特性，考虑其周期性及气温、天气和节假日等影响因素，建立人工鱼群神经网络的预测模型。将人工鱼群神经网络预测模型应用到实际中，研究结果表明人工鱼群神经网络具有预测精度高、误差小的优点，在污水管网监测预警及实现管网与水厂联动等方面具有一定的实际意义。

Forecast of City Sewage Treatment Plant Water Inflow Based on Artificial Fish-Swarm Neural Network

The forecast accuracy of the city sewage treatment plant water inflow has an importantinfluence to the safe operation and scientific management of the sewage plant. The artificial fish algorithm was applied to the training process of the neural net-work. Based onthe change characteristics of the sewage plant inflow contained its cyclical, the influence factors such as tempera-ture, weather and the holidays was considered to establish the forecast model of artificial fish neural network. The artificial fish neural network forecast model was applied to practice, the results show that artificial fish neural network own the advantages of high precision and small error. The method has a certain practical significance in sewage pipe network monitoring,forewarning and realizing pipe network and water linkage.