Daily Natural Gas Load Forecasting Based on a Hybrid Deep Learning Model

Daily Natural Gas Load Forecasting Based on a Hybrid Deep Learning Model

Forecasting daily natural gas load accurately is difficult because it is affected by various factors. A large number of redundant factors existing in the original dataset will increase computational complexity and decrease the accuracy of forecasting models. This study aims to provide accurate forec...

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Bibliographic Details
Main Authors: Nan Wei, Changjun Li, Jiehao Duan, Jinyuan Liu, Fanhua Zeng
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Energies
Subjects:
artificial intelligence (AI)
long short-term memory (LSTM)
principal component analysis (PCA)
natural gas load forecasting
deep learning (DL)
recurrent neural networks (RNN)
Online Access:http://www.mdpi.com/1996-1073/12/2/218

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http://www.mdpi.com/1996-1073/12/2/218

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