Heterogeneous Ensemble Modeling
Heterogeneous Ensemble Modeling is an ensemble learning approach that integrates multiple base learners of different types or algorithms to improve predictive performance by leveraging diverse model architectures and decision mechanisms.
84
Publications
4.1K
Citations
325
Authors
156
Institutions
Publications per year
2017–2026
66
Parents
84
HELAD: A novel network anomaly detection model based on heterogeneous ensemble learning
Ying Zhong, Wenqi Chen, Zhiliang Wang et al. · Computer Networks · 2019 · 171 citations
European summer climate variability in a heterogeneous multi-model ensemble
Pier Luigi Vidale, Daniel Lüthi, Rebekka Wegmann et al. · Climatic Change · 2007 · 136 citations · Full text
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156

Sichuan University
Chengdu, China
4 h-index
8 publications
164 citations
Dalian University of Technology
Dalian, China
3 h-index
6 publications
172 citations

Benha University
Banhā, Egypt
2 h-index
2 publications
92 citations

Beijing University of Technology
Beijing, China
2 h-index
6 publications
127 citations

University of Electronic Science and Technology of China
Chengdu, China
2 h-index
2 publications
187 citations
COMSATS University Islamabad
Islamabad, Pakistan
2 h-index
4 publications
193 citations

Suez University
Suez, Egypt
2 h-index
2 publications
92 citations
Galala University
Suez, Egypt
2 h-index
2 publications
92 citations
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3 publications · 59 citations
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3 publications · 135 citations
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3 publications · 214 citations
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3 publications · 117 citations
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2 publications · 75 citations
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