Feature Selection For Forecasting
Feature Selection for Forecasting is a methodological process in demand forecasting systems that identifies and retains the most relevant predictor variables from a larger set of potential inputs to improve forecast accuracy and model efficiency.
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Publications
37.4K
Citations
2.1K
Authors
832
Institutions
Publications per year
2017–2026
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North China Electric Power University
Beijing, China
15 h-index
52 publications
3.2K citations

Huazhong University of Science and Technology
Wuhan, China
12 h-index
41 publications
3.2K citations

Semnan University
Semnan, Iran
11 h-index
21 publications
2.4K citations
COMSATS University Islamabad
Islamabad, Pakistan
11 h-index
33 publications
2.7K citations

Dongbei University of Finance and Economics
Dalian, China
11 h-index
28 publications
2.6K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
14 publications
1.3K citations
Islamic Azad University Ardabil
Ardabil, Iran
8 h-index
16 publications
2.4K citations

University of Tehran
Tehran, Iran
7 h-index
11 publications
393 citations
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36 publications · 4.1K citations
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32 publications · 1.8K citations
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31 publications · 2.4K citations
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16 publications · 2.2K citations
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