Towards non-intrusive and high accuracy prediction of personal thermal comfort using a few sensitive physiological parameters
作者: Chengcheng ShanJiawen HuJianhong WuAili ZhangGuoliang DingLisa X. Xu
作者单位: 1School of Biomedical Engineering, Shanghai Jiao Tong University, China
2School of Mechanical Engineering, Shanghai Jiao Tong University, China
刊名: Energy & Buildings, 2020, Vol.207
来源数据库: Elsevier Journal
DOI: 10.1016/j.enbuild.2019.109594
关键词: Personal comfort modelThermal sensation predictionIndividual differenceSensitive physiological parametersArtificial neural network
原始语种摘要: Abstract(#br)The existing thermal comfort models that pursue high personal thermal comfort prediction accuracy inevitably cause disturbances because they require data measured from multiple parts of the human body. To address this issue, we proposed the personal thermal comfort prediction method, which realized a high level of prediction performance using no more than 3 physiological parameters (the skin temperatures of the wrist, the neck and the temperature of the point 2 mm above the wrist) by means of an artificial neural network (ANN). This method compares the performance results of the models with different combinations of the measured parameters and determines the optimal personal comfort model (PCM). Human subject experiments were conducted under different ambient conditions,...
全文获取路径: Elsevier  (合作)
影响因子:2.679 (2012)

  • parameters 参数
  • thermal 热的
  • personal 个人
  • prediction 预报
  • comfort 舒适
  • accuracy 准确度
  • physiological 生理的
  • sensation 感觉
  • different 不相同的
  • ambient 外界的