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针对污水流量受降雨径流、管网汇流等自然因素和生活污水、工业废水及泵闸开关等人为因素的影响,具有不确定性、非线性及滞后性,难以建立准确的城市污水泵站系统模型,采用人工神经网络方法建立了城市污水泵站预测模型,通过对污水泵站运行机理过程的理解以及对各变量进行相关性分析从而确定模型的输入,并对不同预见期污水泵站水位进行预测,通过与实际比较及有效性验证,该模型具有较高的精度,可指导城市排水的安全运行控制。
Due to the human factors such as rainfall runoff, pipe network convergence and other natural factors and human sewage, industrial wastewater and pump switch, the sewage flow is uncertain, non-linear and lagged, so it is difficult to establish an accurate urban sewage pumping station system model , The prediction model of urban sewage pumping station was established by using artificial neural network method. The input of the model was confirmed through the understanding of the operating mechanism of sewage pumping station and the correlation analysis of each variable, and the prediction of the water level of the sewage pumping station in different forecast periods Through comparing with actual comparison and validity verification, the model has higher accuracy and can guide the safe operation control of urban drainage.