考虑不确定因素的污水厂日进水量预测法

Forecast of Daily Influent Quantity for Sewage Treatment Plant Considering Uncertain Factors

水量预测对污水处理厂的设计、运行具有非常重要的作用。在研究天气和特别事件因素对污水处理厂进水量影响的基础上 ,充分考虑小时水量变化的日周期性 ,提出了进水量的日周期预测方法 ,建立了水量预测BP网络模型和算法。对某污水处理厂未来日进水量的实际预测结果表明了该方法有效。

Daily influent quantity forecasting plays an important role in the design and operation of a sewage treatment plant. Based on the study of effects of weather factors and special events on the influent quantity, daily periodicity of hourly variation of the influent quantity is given a full consideration. The forecast method of daily periodicity of the influent quantity is presented, and back propagation (BP) model and calculation method are set up. The data from an existing sewage treatment plant was employed to forecast the daily inflow and the result shows that this method is effective.