公开(公告)号：US20190265768A1

公开(公告)日：2019-08-29

申请号：US16284064

申请日：2019-02-25

Applicant: Hefei University of Technology

Inventor： Kaile ZHOU ,  Zhifeng GUO ,  Shanlin YANG ,  Pengtao LI ,  Lulu WEN ,  Xinhui LU

IPC: G06F1/28 ,  G06N20/00 ,  G06N7/00

Abstract: The disclosure provides a method, a system and a storage medium for predicting power load probability density based on deep learning. The method comprises: S101, collecting power load data of a user, meteorological data and air quality data in a preset historical time period, and dividing the collected data into a training set and a test set; S102, determining a deep learning model for predicting power load; S103, inputting the test set into the deep learning model for predicting power load, and obtaining power load prediction data of the user at different quantile points in a third time interval; S104, performing kernel density estimation and obtaining a probability density curve of the power load of the user in the third time interval.