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    ARTICLE

    Energy-Efficiency Model for Residential Buildings Using Supervised Machine Learning Algorithm

    Muhammad Shoukat Aslam1, Taher M. Ghazal2,3, Areej Fatima4, Raed A. Said5, Sagheer Abbas1, Muhammad Adnan Khan6,7,*, Shahan Yamin Siddiqui1,8, Munir Ahmad1

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 881-888, 2021, DOI:10.32604/iasc.2021.017920 - 20 August 2021

    Abstract The real-time management and control of heating-system networks in residential buildings has tremendous energy-saving potential, and accurate load prediction is the basis for system monitoring. In this regard, selecting the appropriate input parameters is the key to accurate heating-load forecasting. In existing models for forecasting heating loads and selecting input parameters, with an increase in the length of the prediction cycle, the heating-load rate gradually decreases, and the influence of the outside temperature gradually increases. In view of different types of solutions for improving buildings’ energy efficiency, this study proposed a Energy-efficiency model for residential More >

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