Comparison of linear regression and artificial neural networks models to predict heating and cooling energy demand, energy consumption and CO₂ emissions

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• 作者：Rafael Pino-Mejí ; as^a ; ^{rafaelp@us.es} ; Alexis Pé ; rez-Fargallo^b ; ^{aperezf@ubiobio.cl} ; Carlos Rubio-Bellido^c ; ^{carlosrubio@us.es} ; Jesú ; s A. Pulido-Arcas^d ; ^{jpulido@ubiobio.cl}
• 关键词：Neural networks ; Energy demand ; Energy consumption ; CO2 emissions ; Energy efficiency
• 刊名：Energy
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：118
• 期：Complete
• 页码：24-36
• 全文大小：1762 K
• 卷排序：118

文摘

Comparison of linear regression and ANN models. Predictive methods for energy demand, consumption and CO2 emissions. Multilayer perceptron accuracy with an R2 coefficient above 99%. Multiple variable iterations on the first stages of building design.