A novel solution for data uncertainty and insufficient in data-driven chiller fault diagnosis based on multi-modal data fusion DOI
Yuwen You, Yuan Zhao, Ke Yan

и другие.

Energy and Buildings, Год журнала: 2024, Номер unknown, С. 115197 - 115197

Опубликована: Дек. 1, 2024

Anomaly Detection Using Convolutional Autoencoder with Residual Gated Recurrent Unit and Weak Supervision for Photovoltaic Thermal Heat Pump System DOI

Lemmon Patrick John,

Sungmin Yoon,

Jiteng Li

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 111694 - 111694

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2
TriChronoNet: Advancing electricity price prediction with Multi-module fusion DOI
Miao He, Weiwei Jiang, Weixi Gu

и другие.

Applied Energy, Год журнала: 2024, Номер 371, С. 123626 - 123626

Опубликована: Июнь 12, 2024

Язык: Английский

Процитировано

14
Accurate and efficient daily carbon emission forecasting based on improved ARIMA DOI

Weiyi Zhong,

Dengshuai Zhai, Wenran Xu

и другие.

Applied Energy, Год журнала: 2024, Номер 376, С. 124232 - 124232

Опубликована: Авг. 22, 2024

Язык: Английский

Процитировано

12
End-to-end residual learning embedded ACWGAN for AHU FDD with limited fault data DOI
Jian Bi, Ke Yan, Yang Du

и другие.

Building and Environment, Год журнала: 2025, Номер 270, С. 112529 - 112529

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

1
A review on hybrid physics and data-driven modeling methods applied in air source heat pump systems for energy efficiency improvement DOI

Yanhua Guo,

Ningbo Wang,

Shuangquan Shao

и другие.

Renewable and Sustainable Energy Reviews, Год журнала: 2024, Номер 204, С. 114804 - 114804

Опубликована: Авг. 14, 2024

Язык: Английский

Процитировано

7
Enhancing And Optimization In Exisiting HVAC Equipment Using Tools Of Industry 4.0 DOI
Feliciano Fraguela, Julio Barreiro Montes, Feliciano Fraguela

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 111924 - 111924

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Enhanced TimesNet algorithm with ConvNext and fusion of time–frequency domain features in fault detection and diagnosis of HVAC systems DOI

Fan Zhong,

Hanfei Yu,

Xiang’e Xie

и другие.

Journal of Building Performance Simulation, Год журнала: 2025, Номер unknown, С. 1 - 16

Опубликована: Фев. 3, 2025

Язык: Английский

Процитировано

0
Total Cost of Ownership Prediction in Chilled Water Plants: Contributing Factors and Role of Artificial Intelligence DOI Creative Commons
Rubaiath E Ulfath, Toh Yen Pang, Ivan Cole

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(3), С. 1618 - 1618

Опубликована: Фев. 5, 2025

This study investigates key parameters and applications of artificial intelligence (AI) in predicting the total cost ownership (TCO) for chilled water plants (CWPs). Forecasting TCO CWPs is challenging due to diverse dynamic factors that influence it, necessitating understanding their complex correlations causations. While AI non-AI approaches have improved parameter prediction accuracy different engineering applications, comprehensive literature reviews on chiller methodologies influencing are limited. systematic review addresses three objectives: (1) identify estimating CWPs, (2) examine existing techniques employed forecasting benefits energy savings, (3) evaluate how enhances robustness. Following preferred reporting items meta-analyses (PRISMA) guidelines, this analyzed studies from 2017 2024 sourced Web Science Scopus databases. identifies several TCO, including cooling load, consumption, capacity, Coefficient Performance (COP). The shows AI-driven models, such as deep learning machine algorithms, robustness predictions, it further demonstrates scenarios where outperforms conventional methods. Notably, current predicted be capable reducing life cycle costs by up 18%, based modeling estimates.

Язык: Английский

Процитировано

0
AI-Driven Design Optimization for Sustainable Buildings: A Systematic Review DOI Creative Commons

Piragash Manmatharasan,

Girma Bitsuamlak, Katarina Grolinger

и другие.

Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115440 - 115440

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Adaptive human-computer interaction for industry 5.0: A novel concept, with comprehensive review and empirical validation DOI Creative Commons
Rania Hamdani, Inès Chihi

Computers in Industry, Год журнала: 2025, Номер 168, С. 104268 - 104268

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0