以客观指标为输入参数的织物热湿舒适性预测

Fabric Thermal Moisture Comfort Prediction Based on Objective Indicators as Input Parameters

探讨以客观指标为输入参数的织物热湿舒适性预测效果.测试了36种针织试样的6个静态客观热湿舒适性评价指标以及4个主观热湿舒适性评价指标,利用BP神经网络的方法建立了以静态客观评价指标为输入参数、以主观评价指标为输出参数的织物热湿舒适性预测模型.应用该模型对其中8种针织试样进行检验和分析,预测结果表明：该模型能有效地预测织物的主观热湿舒适性,其预测绝对误差范围在0.04 ～1.25间.

Fabric thermal moisture comfort prediction effect based on objective indicators as input parameters was discussed.Thirty-six knitting fabrics were tested including six static thermal moisture comfort objective evaluations and four thermal moisture comfort subjective evaluations.BP neural network was used to establish fabric thermal moisture comfort prediction model that taking static objective evaluation indexes as input parameter,taking subjective evaluations indexes as output parameter.Eight kinds of knitting fabric were tested and analyzed by the model.The prediction shows that fabric thermal moisture comfort can be predicted by the model effectively,the prediction absolute error range is 0.04to 1.25.