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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：多元回归预测热沙漠气候下混合居住区住宅建筑的采光和能耗

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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：在最近几十年中，埃及经历了前所未有的城市住宅区增长，导致室内环境质量恶化。这项研究是正在进行的具有不同物理配置和立面的建筑性能研究的一部分。它旨在量化亚历山大热沙漠混合居民区中住宅建筑的采光和能耗。该方法论方法涉及执行计算模拟以构建涵盖多个影响因素的数据集，这些数据被用来开发多元线性回归模型。这产生了五个方程，可以用作预测设计早期阶段建筑性能的代理。对开发的模型进行了验证，发现预测数据以及微小的误差与仿真结果非常吻合，表明这些模型可以解释建筑物性能的变化。这些措施在残差的附加分析的支持下，确定了所选变量的强度以及已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严重阻碍环境和立面配置的因素​​来评估建筑的初步性能，而无需进行详尽的分析。

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