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Prediction of energy consumption in hotel buildings via support vector machines

Datos Bibliográficos

ID21233604
AutoresMinglei Shao (University of Shanghai for Science and Technology), Xin Wang (0000-0003-2833-6940, University of Shanghai for Science and Technology, autor de correspondencia), Zhen Bu (0000-0001-8743-8467, Shanghai Research Institute of Building Sciences (China)), Xiaobo Chen (0000-0001-9940-1637, University of Shanghai for Science and Technology), Yuqing Wang (0000-0002-1691-8161, Shanghai Research Institute of Building Sciences (China))
Año2020
Volumen57
Páginas102128
Fecha de publicación2020-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSustainable Cities and Society (JOURNAL)
Identificadores de la revistaISSN: 2210-6707 • E-ISSN: 2210-6715
EditorialElsevier BV (PUBLISHER)
DOI10.1016/j.scs.2020.102128
OpenAlexW3010335229
IdiomaEN
Citas recibidas11
Referencias citadas23

Energy consumption · Kernel method · Machine learning · Outlier · Radial basis function kernel · Statistics · Support vector machine · Building Energy and Comfort Optimization · Computer Science · Energy Load and Power Forecasting · Engineering · Mathematics · Urban Heat Island Mitigation · Artificial Intelligence

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  • Revealing building operating carbon dynamics for multiple cities

    Open Access•Winston Yap, Abraham Noah Wu et al.•Nature Sustainability•2025

  • Libsvm

    Open Access•Chih-Chung Chang, Chih-Jen Lin et al.•ACM Transactions on Intelligent…•2011

  • Multiple power-based building energy management system for efficient management of building energy

    Open Access•Seok-Ho Yoon, Seungyeon Kim et al.•Sustainable Cities and Society•2018

Obras citantes distintas11
Citas por año2,2
Intervalo de citas2021 - 2025 (5)
Velocidad de citaciónrecent
Altamente citadoNo
Tipos de citaNeutras: 11
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