大型公共建筑室内热舒适性预测方法研究  

Study on Indoor Thermal Comfort Prediction Method of Large-scale Public Building

作　　者：张晓亚[1] 于军琪[1] 王睿 

机构地区：[1]西安建筑科技大学信息与控制工程学院,陕西西安710055 [2]中联西北工程设计研究院,陕西西安710082

出　　处：《现代建筑电气》2013年第2期13-17,29,共6页Modern Architecture Electric

基　　金：陕西省教育厅专项科研项目(11JK1041);住房和城乡建设部项目(2012-K1-1)

摘　　要：针对大型公共建筑室内热环境实时控制问题,运用T-S模糊神经网络理论与方法,建立了大型公共建筑室内热舒适性PMV指标的预测模型。通过对实例的分析与评价,验证了该模型的合理性。与传统BP算法的对比表明,该方法计算速度快、准确度高,为解决基于PMV指标的空调实时控制奠定了基础。Due to the problem of controling the indoor thermal environment for large-scale public buildings in real- time, the prediction model of indoor thermal comfort PMV index for the large-scale public buildings was established using T - S fuzzy neural network theory and method. After analysis and evaluation, the reasonableness of this model was verified. By comparing the result with BP algorithm, it indicated that the method can accurately predict PMV value and tile calculation speed is high. It lays the first stone for the real-time control of HVAC system basde on PMV index.

关 键 词：大型公共建筑 T—S模糊神经网络 热舒适 PMV指标 预测 

分 类 号：TU831[建筑科学—供热、供燃气、通风及空调工程]