Improving energy absorption capacity in a thermal energy storage system for domestic heating applications using an integrated machine learning/numerical approach
Xianzhi TangSchool of Civil Engineering, Chongqing Vocational Institute of Engineering, Chongqing 402260, ChinaXin SunCollege of Urban Construction, Zhejiang Shuren University, Hangzhou 310015 Zhejiang Province, ChinaSinan Q. SalihMohamed ShabanDepartment of Physics, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi ArabiaSarminah SamadDepartment of Management, College of Business Administration, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi ArabiaAhmad AlmadhorDepartment of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf University, Saudi ArabiaFahad M. AlhomayaniApplied College, Taif University, Saudi ArabiaNargiza KamolovaDepartment of Chemistry and Its Teaching Methods, Tashkent State Pedagogical University, Tashkent, UzbekistanMouloud AoudiaDepartment of Industrial Engineering, College of Engineering, Northern Border University, P.O. Box 1321, Arar 91431, Saudi ArabiaSalem AlkhalafDepartment of Computer Engineering, College of Computer, Qassim University, Buraydah, Saudi Arabia
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