Hybrid Load Forecasting
Hybrid Load Forecasting is a load forecasting methodology that integrates multiple distinct modeling techniques—such as statistical, machine learning, and deep learning approaches—within a unified framework to leverage their complementary strengths and improve prediction accuracy.
309
Publications
20.7K
Citations
1K
Authors
404
Institutions
Publications per year
2017–2026
201
Parents
309
Feifei He, Jianzhong Zhou, Zhong-kai Feng et al. · Applied Energy · 2019 · 338 citations
Computing, Meteorology, Forecasting +15
1–5 of 309
1K
Asia Eastern University of Science and Technology, Taiwan
12 publications · 974 citations
12
h-index
8
h-index
5
h-index
5
h-index
University of Engineering and Technology Lahore, Pakistan
4 publications · 174 citations
4
h-index
1–5 of 1K
404

North China Electric Power University
Beijing, China
16 h-index
46 publications
5K citations

Dongbei University of Finance and Economics
Dalian, China
10 h-index
21 publications
942 citations

Asia Eastern University of Science and Technology
Taipei, Taiwan
8 h-index
9 publications
616 citations
Lanzhou University
Lanzhou, China
7 h-index
20 publications
893 citations
National University of Singapore
Singapore, Singapore
6 h-index
10 publications
610 citations

University of Engineering and Technology Lahore
Lahore, Pakistan
6 h-index
11 publications
710 citations
Tsinghua University
Beijing, China
5 h-index
15 publications
903 citations

Zhejiang University
Hangzhou, China
5 h-index
12 publications
549 citations
1–8 of 404
32 publications · 2.1K citations
24
h-index
21 publications · 1.5K citations
20
h-index
15 publications · 1.7K citations
15
h-index
13 publications · 2K citations
13
h-index
11 publications · 1.8K citations
10
h-index
1–5