Journal of Applied Science and Engineering

Published by Tamkang University Press

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Adaptive Approaches in Urban Architectural Design for Enhancing Energy-Conscious Performance

 2027

 Volume 36

Hefang Xu

Henan Technical College of Construction, Zhengzhou, Henan, 450000, China

Received: August 6, 2025
Accepted: July 15, 2026
Publication Date: October 09, 2026

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The correlation matrix of features for type A

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Estimation of energy consumption in urban areas, particularly in relation to the Universal Thermal Climate Index, and related environmental factors associated with architectural design, has remained an essential challenge in the related field of urban planning. This study, holding interest in the first three advanced algorithms, namely HGBR, CatBoost, and LightGBM, was proposed to explore related possibilities in using machine learning algorithms for estimation. The used algorithms were analyzed using three different architectural setups (types A, B, and C) that were optimized using the HGS optimization algorithm. The obtained results clearly highlight that the HGBR-HGS system was significantly accurate for type A buildings for cooling load calculations and estimates related to the Universal Thermal Climate Index. The CatBoost-HGS system performed better than the HGBR-HGS system for type B buildings, again forming the top-performing system for cooling loads. Type C buildings also followed similar lines, where again the CatBoost-HGS system performed better for calculations related to Universal Thermal Climate Index, while the HGBR-HGS system again formed the top-performing system for cooling loads. The results demonstrate that the HGBR-HGS model achieved superior performance, with R² values reaching up to 0.9994 for cooling load prediction and 0.9880 for UTCI estimation, along with the lowest RMSE values across most scenarios. Additionally, the CatBoost-HGS model exhibited strong performance in predicting UTCI, achieving R² values up to 0.9875 for specific building types.

Keywords: Cooling loads, Universal Thermal Climate Index, LightGBM, CatBoost, HGBR, HGS

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