摘要
以室内空气环境参数设计值与标准值的均方根误差 (适应度 )为基础 ,建立了三个优化目标 ,即 :使室内指定区域空气环境参数适应度达到最小、室内空气环境参数适应度满足要求的区域达到最大、室内分区域空气环境参数适应度达到最小。应用CFD技术 ,结合进化神经算法 ,建立考虑多因素影响的、实现上述优化目标的室内空气环境设计方案预测。
Based on the root-mean-square deviation (i.e. adaptation degree) of design value and standard value of indoor air environment parameters, sets up three optimization objectives namely the minimum adaptation degree in given region, the maximum area with the good adaptation degree and the minimum adaptation degree in sub-region. By way of CFD technology and an evolution-nerve calculation method, develops a computer method to forecast, analyze and evaluate the design schemes of indoor air parameters for realizing the optimization objectives which adapting multi-factors.
出处
《暖通空调》
北大核心
2004年第11期128-130,共3页
Heating Ventilating & Air Conditioning
基金
中国科学院大气物理所LAPC基金资助项目 (编号 :LAPCKF 2 0 0 3 12 )
