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MULTIVARIATE PREDICTIVE WINDOW BLIND CONTROL MODELS FOR INTELLIGENT BUILDING FACADE SYSTEMS

机译:智能建筑立面系统的多变量预测窗帘控制模型

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This paper presents results from a window blind usage field study that was conducted in California USA In this study., the measurements of physical environmental conditions were cross-linked with participants' window blind controlling preferences (n=83) A total of seven predictive window blind control multivariate logistic models were derived As hypothesized, the probability of a window blind closing event increased as the magnitude of phy sical environmental and confounding factors increased (p < 01) The main predictors were window/ background luminance level and vertical solar radiation at the window The confounding factors included MRT, direct solar penetration, and participants' self-reported sensitivity to brightness The results showed that the models correctly predict between 84 - 89 % of the observed window blind control behavior This research extends the knowledge of how and why building occupants manually control window blinds in private offices, and provides results that can be directly implemented in energy simulation programs.
机译:本文展示的是在美国加利福尼亚州进行了这项研究百叶窗的使用领域的研究成果,物理环境条件下的测量结果与参与者的窗帘控制喜好交联(N = 83)共有7个预测窗口盲控制多变量逻辑模型得出作为假设,百叶窗关闭事件的概率增大的PHY SICAL环境和混杂因素的大小增加(p <0.01)的主要预测因子为窗口/背景亮度水平和垂直的太阳辐射在窗口混杂因素包括地铁,直接的阳光穿透,以及参与者的自我报告的敏感性亮度结果表明,该模型正确预测84之间 - 观察到的百叶窗帘的控制行为的89%,这项研究扩展如何以及为什么建设知识乘员手动控制在私人办公室的窗帘,并提供结果,其中可可在能量仿真程序直接实现。

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