基于综合权重因子的城市时需水量预测

Prediction of Urban Hourly Water Demand Based on Synthetic Weight Factor

摘要:

提出了基于综合权重因子的城市时需水量预测方法。根据预测日前几日和前几周的用水量数据，计算平均时用水量；引入综合权重因子，构建预测日前1日时用水量模型。结合日需水量预测数据，将获得的最优连续日数、最优连续周数和综合权重因子，用于预测日的时需水量预测。算例验证结果表明，预测值平均绝对百分比误差较小。

Abstract:

A prediction method of urban hourly water demand based on synthetic weight factor is proposed. According to the water consumption data of the days and weeks before the forecasting day， the average hourly water consumption is calculated. Then， the synthetic weight factor is introduced to construct the water consumption model of the day before the forecasting day. Combined with the daily water demand forecasting data， the optimal continuous days， the optimal continuous weeks and the synthetic weight factors are used to forecast the hourly water demand of the forecasting day. The case study shows that the average absolute percentage error of the predicted values is small.