供电服务中心话务量受到多种因素影响。首先分析了供电服务中心话务水平和话务曲线特性，确定工作日与周六、周日星期类型对话务量的影响。在此基础上分析温度、降水对话务量的影响，确定平均温度、最低温度和逐时降水量是影响话务量的关键因素，尤其是降水量是影响话务曲线突变的重要指标。考虑到降水日和非降水日的区别，提出了分层相似预测法，即将话务曲线分成基础话务曲线和特征话务值，对于非降水日，基础话务曲线即为预测曲线，对于降水日，将特征话务量值进行叠加形成预测曲线。实例验证了所提方法的正确性和有效性。所做工作对提高供电服务中心话务量预测精度，指导中心优化排班具有重要现实意义和实用价值。%There are many factors which influence the telephone traffic of power supply service center. This paper firstly analyzes the level and the curve shape of the traffic to prove the effect of the type of weeks. Then this paper determines the average temperature, minimum temperature and hourly precipitation data are the other key factors of the development and change of the traffic, especially precipitation is the most important indicator of the curve mutation. Taking into account the difference between the precipitation days and non-precipitation days, the paper proposes a layered similar forecasting method which divides the forecasting result into basic traffic curves and traffic quantity. The basic curve is the predicted result for non-precipitation days, and the traffic quantity and basic traffic curves are superimposed to form the prediction result for precipitation days. A case is given to demonstrate the effectiveness of the method described. The paper’s work can improve traffic forecasting accuracy of power supply service center, which has significant applicable value for optimized scheduling.
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