A Deep Learning Neural Network for the Residential Energy Consumption Prediction-Reference-Cited by-同舟云学术

A Deep Learning Neural Network for the Residential Energy Consumption Prediction

Published:2022-01-10 Issue:4 Volume:17 Page:575-582
ISSN:1931-4973
Container-title:IEEJ Transactions on Electrical and Electronic Engineering
language:en
Short-container-title:IEEJ Transactions Elec Engng

Author:

Huang Jinhai¹^ORCID,Pang Chengxin¹^ORCID,Yang Weijun¹^ORCID,Zeng Xinhua²^ORCID,Zhang Jun³,Huang Chizhi³

Affiliation:

1. College of Electronical Engineering Shanghai University of Electric Power Pudong New District Shanghai 201306 China

2. Academy for Engineering and Technology Fudan University Shanghai 200433 China

3. Distribution network operation and maintenance department, Nari Technology Nanjing Control Systems Co., Ltd Nanjing Jiangsu Province 211106 China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tee.23543

Reference38 articles.

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3. Predictive analysis on electric-power supply and demand in China

4. A review on time series forecasting techniques for building energy consumption

5. Multistep wind speed and wind power prediction based on a predictive deep belief network and an optimized random forest;Sun Z;Mathematical Problems in Engineering,2018

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