Open AccessOptimization Analysis of Parametric passive Energy-saving Design for Residential Buildings
Author(s) -
Meng Tang,
Hui Zhang,
Jingyi Han
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/782/5/052046
Subject(s) - genetic algorithm , parametric statistics , artificial neural network , computer science , parametric design , passive house , parametric model , energy (signal processing) , research object , scheme (mathematics) , plot (graphics) , architectural engineering , efficient energy use , engineering , artificial intelligence , machine learning , mathematics , statistics , geography , mathematical analysis , regional science , electrical engineering
Taking residential building in hot summer and cold winter area as research object, this paper established a model based on passive energy-saving design, and combined artificial neural network(ANN) and genetic algorithm(GA) models to analyze lighting, sunlight, and plot ratio,etc.. In addition, for the experimental test of multiple sets of data samples, the optimized passive design combination scheme was sought to verify the possibility of parametric optimization design based on genetic algorithm(GA).