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A multivariate regression to predict daylighting and energy consumption of residential buildings within hybrid settlements in hot-desert climates

机译:多元回归,以预测热沙漠气候混合居所内的住宅建筑物的日光和能耗

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摘要

Over recent decades, Egypt has experienced unprecedented growth of urban residential regions causing deterioration to indoor environmental quality. This research is a part of an ongoing study of building performance with different physical configurations and facades. It aims to quantify the daylighting and energy consumption of residential buildings in the hot-desert hybrid settlements of Alexandria. The methodological approach involves performing computational simulations to construct a dataset covering several influencing factors, which are exploited to develop multivariate linear regression models. This yields five equations used as proxies for predicting building performance in the early stages of the design. The developed models are validated and the predicted data, accompanied by insignificant errors, are found to be in a good agreement with simulation results, indicating that these models can explain the variation in the building performance. These measures, supported by an additional analysis of residuals, confirm the strength of selected variables and suitability of developed models to fit the dataset. This can aid architects and decision makers to assess a preliminary building performance by considering factors of heavily obstructed environment and facade configurations without the need to perform exhaustive analysis.
机译:近几十年来,埃及经历了城市住宅区的前所未有的增长,导致室内环境质量恶化。本研究是持续研究建立不同的物理配置和外墙的持续研究。它旨在量化在亚历山大的热沙漠混合沉降中的住宅建筑的日光和能耗。该方法方法涉及执行计算模拟以构建覆盖若干影响因素的数据集,该数据集被利用以开发多变量线性回归模型。这产生了五个方程,用于预测设计早期阶段的建筑性能。已验证开发的模型,并伴随着无关头差的预测数据,发现与仿真结果很好,表明这些模型可以解释建筑物性能的变化。这些措施通过对残差的额外分析支持,确认所选变量的强度和开发模型适合数据集的适用性。这可以帮助建筑师和决策者通过考虑受阻环境和外立面配置的因素​​来评估初步建筑性绩效,而无需进行详尽分析。

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