Yanhua Lu1, Xuehui Gong2,*, Andrew Byron Kipnis3
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5481-5497, 2022, DOI:10.32604/cmc.2022.027089
Abstract Combined with the energy consumption data of individual buildings in the logistics group of Yangtze University, the analysis model scheme of energy consumption of individual buildings in the university is studied by using Back Propagation (BP) neural network to solve nonlinear problems and have the ability of global approximation and generalization. By analyzing the influence of different uses, different building surfaces and different energy-saving schemes on the change of building energy consumption, the grey correlation method is used to determine the main influencing factors affecting each building energy consumption, including uses, building surfaces and energy-saving schemes, which are used as… More >
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