Research on the Design Strategy of Double–Skin Facade in Cold and Frigid Regions—Using Xinjiang Public Buildings as an Example DOI Open Access
Xiang Liu,

Wanjiang Wang,

Yingjie Ding

и другие.

Sustainability, Год журнала: 2024, Номер 16(11), С. 4766 - 4766

Опубликована: Июнь 3, 2024

In the context of global warming, focus on applying and researching double–skin facade (DSF) systems to reduce energy consumption in buildings has significantly increased. However, researchers have not thoroughly examined performance applicability DSFs severe cold regions with high winter heating demands. This study aims evaluate potential application harsh cities Northwest China investigate their role enhancing efficiency large public buildings. Through simulation a comprehensive evaluation using TOPSIS entropy weight method, effects 20 DSF schemes four Xinjiang (Kashgar, Urumqi, Altay, Turpan) were analyzed. The experimental results indicate that average EUI energy–saving rates Kashgar, Turpan are 64.75%, 63.19%, 56.70%, 49.41%, respectively. South–facing orientation is deemed optimal for cities, highest rate reaching 15.19%. benefits west–facing surpass those north–facing DSF. Conversely, order other south, north, west, east. An analysis heating, cooling, lighting reveals Box Windows exhibit superior efficiency, while Corridors more effective cooling. characteristic also evident installation various types curtain walls. Given relatively higher demand compared cooling urban areas, yields significant when facing or north; conversely, if there should be considered these three directions. Multistorey suitable east–facing cities. Selecting based specific conditions requirements can building consumption. research findings offer theoretical guidance designing implementing diverse regions.

Язык: Английский

A systematic review and comprehensive analysis of building occupancy prediction DOI
Tao Li, Xiangyu Liu, Guannan Li

и другие.

Renewable and Sustainable Energy Reviews, Год журнала: 2024, Номер 193, С. 114284 - 114284

Опубликована: Янв. 16, 2024

Язык: Английский

Процитировано

25

Optimization and prediction of energy consumption, light and thermal comfort in teaching building atriums using NSGA-II and machine learning DOI
Zhengshu Chen,

Yanqiu Cui,

Haichao Zheng

и другие.

Journal of Building Engineering, Год журнала: 2024, Номер 86, С. 108687 - 108687

Опубликована: Янв. 30, 2024

Язык: Английский

Процитировано

21

Acoustic Insulation Optimization of Walls and Panels with Functional Graded Hollow Sections Using Graph Transformer Evaluator and Probability-Informed Genetic Algorithm DOI Creative Commons
Hanmo Wang, Tam H. Nguyen, Zhong-Rong Lu

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 112550 - 112550

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

3

Attention-LSTM architecture combined with Bayesian hyperparameter optimization for indoor temperature prediction DOI

Ben Jiang,

Hongwei Gong,

Haosen Qin

и другие.

Building and Environment, Год журнала: 2022, Номер 224, С. 109536 - 109536

Опубликована: Авг. 30, 2022

Язык: Английский

Процитировано

53

Building Energy Prediction Models and Related Uncertainties: A Review DOI Creative Commons
Jiaqi Yu, Wen‐Shao Chang, Yu Dong

и другие.

Buildings, Год журнала: 2022, Номер 12(8), С. 1284 - 1284

Опубликована: Авг. 21, 2022

Building energy usage has been an important issue in recent decades, and prediction models are tools for analysing this problem. This study provides a comprehensive review of building uncertainties the models. First, paper introduces three types methods: white-box models, black-box grey-box The principles, strengths, shortcomings, applications every model discussed systematically. Second, analyses terms human, building, weather factors. Finally, research gaps predicting consumption summarised order to guide optimisation methods.

Язык: Английский

Процитировано

50

Data-driven prediction and optimization of residential building performance in Singapore considering the impact of climate change DOI
Hainan Yan,

Guohua Ji,

Ke Yan

и другие.

Building and Environment, Год журнала: 2022, Номер 226, С. 109735 - 109735

Опубликована: Окт. 28, 2022

Язык: Английский

Процитировано

46

A spatial-temporal layer-wise relevance propagation method for improving interpretability and prediction accuracy of LSTM building energy prediction DOI
Guannan Li, Fan Li,

Chengliang Xu

и другие.

Energy and Buildings, Год журнала: 2022, Номер 271, С. 112317 - 112317

Опубликована: Июль 16, 2022

Язык: Английский

Процитировано

45

A dynamic intelligent building retrofit decision-making model in response to climate change DOI

Dingyuan Ma,

Xiaodong Li, Borong Lin

и другие.

Energy and Buildings, Год журнала: 2023, Номер 284, С. 112832 - 112832

Опубликована: Янв. 31, 2023

Язык: Английский

Процитировано

34

Utilizing interpretable stacking ensemble learning and NSGA-III for the prediction and optimisation of building photo-thermal environment and energy consumption DOI

Yeqin Shen,

Yubing Hu, Kai Cheng

и другие.

Building Simulation, Год журнала: 2024, Номер 17(5), С. 819 - 838

Опубликована: Фев. 23, 2024

Язык: Английский

Процитировано

13

A multi-objective optimization framework for performance-based building design considering the interplay between buildings and urban environments DOI

Zhaoyang Qiu,

Qiaoqiao Yong,

Jiayuan Wang

и другие.

Energy Conversion and Management, Год журнала: 2024, Номер 315, С. 118793 - 118793

Опубликована: Июль 15, 2024

Язык: Английский

Процитировано

9