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Prediction of building energy performance using mathematical gene-expression programming for a selected region of dry-summer climate

Author name : elsayed aly bastawisy sawsan
Publication Date : 2023-11-01
Journal Name : Engineering Applications of Artificial Intelligence

Abstract

Developing energy-efficient buildings considering building design parameters can help reduce buildings' energy consumption. The energy efficiency of residential buildings is considered a top priority for the energy policies of a country. Thus, this study utilizes gene-expression programming (GEP) to estimate the energy performance of residential buildings. The energy consumption evaluations were carried out using the Etotect energy simulation software. Eight building parameters with 768 data points were considered to generate the database for the heating load (HL) and cooling load (CL), including relative compactness, surface area, wall area, roof area, overall building height, glazing orientation, glazing area, and distribution of glazing area. Different GEP predictive models with varying parameters for building HL and CL were developed, and the best-performing prediction model was selected. In addition

Keywords

building energy performance,dry-summer climate

Publication Link

https://doi.org/10.1016/j.engappai.2023.106958

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