摘要
在月用电量数据缺失问题的预处理方法中,如何使预处理的数据更接近原数据,一直是研究的重点内容。采用分箱灰色预测的方法,先将月用电量数据进行分箱处理,再用灰色预测方法进行线性填补,最终得到填补后的月用电量数据。
In the pretreatment of data loss in monthly electricity consumption, one of the important things is how to make preprocessing data closer to the original data. Makes the monthly electricity consumption apart first, and predicts the losing data by grey prediction and finally obtains the monthly electricity consumption.
