Solar Energy and Building Physics Laboratory, Ecole Polytechnique Fédérale de Lausanne.
Int J Biometeorol. 2011 Sep;55(5):681-94. doi: 10.1007/s00484-010-0383-4. Epub 2011 Feb 25.
Based on results from a field survey campaign conducted in Switzerand, we show that occupants' variations in clothing choices, which are relatively unconstrained, are best described by the daily mean outdoor temperature and that major clothing adjustments occur rarely during the day. We then develop an ordinal logistic model of the probability distribution of discretised clothing levels, which results in a concise and informative expression of occupants' clothing choices. Results from both cross-validation and independent verification suggest that this model formulation may be used with confidence. Furthermore, the form of the model is readily generalisable, given the requisite calibration data, to environments where dress codes are more specific. We also observe that, for these building occupants, the prevailing metabolic activity levels are mostly constant for the whole range of surveyed environmental conditions, as their activities are relatively constrained by the tasks in hand. Occupants may compensate for this constraint, however, through the consumption of cold and hot drinks, with corresponding impacts on metabolic heat production. Indeed, cold drink consumption was found to be highly correlated with indoor thermal conditions, whilst hot drink consumption is best described by a seasonal variable. These variables can be used for predictive purposes using binary logistic models.
基于在瑞士进行的实地调查活动的结果，我们表明，相对不受限制的穿着者在服装选择上的变化可以用日平均室外温度来很好地描述，而且在白天很少会进行重大的服装调整。然后，我们开发了一个离散服装层次概率分布的有序逻辑模型，这为穿着者的服装选择提供了简洁而有信息量的表达。交叉验证和独立验证的结果表明，该模型公式可以自信地使用。此外，只要有必要的校准数据，该模型的形式就可以很容易地推广到着装要求更具体的环境中。我们还观察到，对于这些建筑内的居住者来说，在调查的整个环境条件范围内，他们的新陈代谢活动水平大多保持不变，因为他们的活动受到手头任务的相对限制。然而，居住者可以通过饮用冷、热饮料来补偿这种限制，这会对新陈代谢产生的热量产生相应的影响。事实上，冷饮料的消费与室内热条件高度相关，而热饮料的消费则最好用季节性变量来描述。这些变量可以使用二元逻辑模型进行预测。
