An integrated D-CNN-LSTM approach for short-term heat demand prediction in district heating systems

An integrated D-CNN-LSTM approach for short-term heat demand prediction in district heating systems

Forecasting short-term heat demand is an integral function of district energy management applications. Although some well-known methods, such as support vector machine and artificial neural networks, can be employed, most of them require additional variables (such as temperature and humidity) in add...

Full description

Bibliographic Details
Main Authors: Fulong Yao, Wenju Zhou, Mostafa Al Ghamdi, Yang Song, Wanqing Zhao
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Energy Reports
Subjects:
Time series prediction
CNN
LSTM
Heat demand
Sequence differencing
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484722015311

Internet

http://www.sciencedirect.com/science/article/pii/S2352484722015311

Similar Items