A hybrid ensemble learning framework for zero-energy potential prediction of photovoltaic direct-driven air conditioners DOI
Chujie Lu, Sihui Li, Junhua Gu

и другие.

Journal of Building Engineering, Год журнала: 2022, Номер 64, С. 105602 - 105602

Опубликована: Ноя. 24, 2022

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

21

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

19

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

2

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

51

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

48

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

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

42

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

32

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

10

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