制冷与空调（四川）
製冷與空調（四川）
제랭여공조（사천）
REFRIGERATION & AIR-CONDITION
2011年
5期
443-448
,共6页
王萌%魏彩欣%吴佐莲%刘小春%刘惠%黄冠豪
王萌%魏綵訢%吳佐蓮%劉小春%劉惠%黃冠豪
왕맹%위채흔%오좌련%류소춘%류혜%황관호
工位空调%PMV%人工神经网络%预测%模型
工位空調%PMV%人工神經網絡%預測%模型
공위공조%PMV%인공신경망락%예측%모형
Task Air-conditioning%PMV%Artificial Neural Network%Predict%Model
建立了预测工位空调微环境热舒适指标PMV的人工神经网络模型。模型的7938组输入向量数据选自ISO7730中推荐的PMV及其参数范围,并考虑工作位形成的微环境的参数区间,以及ASHRAE标准舒适区域。编制程序计算出输入向量对应的PMV值作为模型的输出量。对网络进行训练和测试的结果表明,用人工神经网络建立的模型能够迅速准确地预测工位空调微环境的热舒适指标PMV。
建立瞭預測工位空調微環境熱舒適指標PMV的人工神經網絡模型。模型的7938組輸入嚮量數據選自ISO7730中推薦的PMV及其參數範圍,併攷慮工作位形成的微環境的參數區間,以及ASHRAE標準舒適區域。編製程序計算齣輸入嚮量對應的PMV值作為模型的輸齣量。對網絡進行訓練和測試的結果錶明,用人工神經網絡建立的模型能夠迅速準確地預測工位空調微環境的熱舒適指標PMV。
건립료예측공위공조미배경열서괄지표PMV적인공신경망락모형。모형적7938조수입향량수거선자ISO7730중추천적PMV급기삼수범위,병고필공작위형성적미배경적삼수구간,이급ASHRAE표준서괄구역。편제정서계산출수입향량대응적PMV치작위모형적수출량。대망락진행훈련화측시적결과표명,용인공신경망락건립적모형능구신속준학지예측공위공조미배경적열서괄지표PMV。
Artificial Neural Network Model for predicting thermal comfort index PMV about local environment created by Task Air-Conditioning system was developed in this article.The 7938 groups of studying and testing data samples were chosen from the parameters recommended by ISO 7730,considering the parameter intervals of local environment in the workstations,as well as the standard thermal comfort regions of ASHRAE.Outputs of the model were the PMV values calculated by computer program.The results of training and testing indicated that the ANN model could predicate PMV quickly and accurately.
