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Development of an adaptation table to enhance the accuracy of the predicted mean vote model

机译:开发适应表以增强预测平均投票模型的准确性

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The Predicted Mean Vote (PMV) model is extensively used by current thermal comfort standards, such as ASHRAE 55 and ISO 7730, despite its discrepancy in predicting Thermal Sensation (TS). The implicit assumption is that PMV can be applied for predicting TS of a large population. Our statistical analysis of a subset of ASHRAE global database of thermal comfort field study shows that occupants' expectations towards TS are affected by factors that are not accounted for in the classic PMV model, such as climate, building type, age group, season and gender. The influences of the climate and building type are more determinant. An adapted PMV (PMVa) model and an adaptation table were developed based on the selected samples to reduce this discrepancy. After adaptation, the medians of each category corresponding to the discrepancy are zero or near zero. The results also show that the adapted PMV outperforms the classic PMV in predicting TS, while increasing the overall accuracy from 36% to 39%.
机译:预测的平均投票(PMV)模型被当前热舒适度标准广泛使用,例如ASHRAE 55和ISO 7730,尽管其在预测热敏(TS)时差异。隐式假设是PMV可以应用于预测大群的TS。我们对热舒适田间研究的Ashrae全球数据库子集的统计分析表明,占用者对TS的期望受到在经典PMV模型中未占的因素的影响,例如气候,建筑类型,年龄组,季节和性别。气候和建筑类型的影响更为决定例。基于所选样品开发了一种适应的PMV(PMVA)模型和适配表,以减少这种差异。在自适应之后,对应于差异的每个类别的中位数为零或接近零。结果还表明,适应的PMV在预测TS中优于经典的PMV,同时将整体精度从36%增加到39%。

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