Jiang, Kaiyun and Shi, Tianyu and Yu, Haowei and Mahyuddin, Norhayati and Lu, Shifeng (2024) A systematic review of multi-output prediction model for indoor environment and heating, ventilation, and air conditioning energy consumption in buildings. Indoor and Built Environment, 33 (9). pp. 1574-1604. ISSN 1420-326X, DOI https://doi.org/10.1177/1420326X241258678.
Full text not available from this repository.Abstract
Heating, ventilation and air conditioning (HVAC) systems could significantly impact indoor environmental quality, particularly in terms of thermal comfort and indoor air quality. Achieving a high-quality indoor environment poses challenges to the energy consumption of HVAC systems. Thus, balancing thermal comfort, indoor air quality (IAQ) and energy consumption becomes a challenging task. Currently, indoor environment prediction methods are considered effective solutions to address this issue. However, the published literature usually concentrates on single aspects like thermal comfort, air quality or energy consumption, with multi-aspect prediction methods being rare. The present work reviews research spanning the last decade that employs machine learning methods for predicting indoor environments and HVAC energy consumption through separate and multi-output predictive models. Separate predictive models focus on HVAC systems' impact on the indoor environment, while multi-output models consider the interplay of various outputs. This article gives a thorough insight into machine learning prediction models' workflow, detailing data collection, feature selection and model optimization for each research goal. A systematic assessment of methods for data collection of diverse prediction targets, machine learning algorithms and validation approaches for different prediction models is presented. This review highlights the complexities of data management, model development and validation, enriching the knowledge base in indoor environmental quality optimization.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Prediction model; indoor air quality; thermal comfort; heating, ventilation and air conditioning building; heating, ventilation and air conditioning energy consumption |
| Subjects: | T Technology > TD Environmental technology. Sanitary engineering T Technology > TH Building construction |
| Divisions: | Faculty of the Built Environment |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 16 Jan 2025 01:46 |
| Last Modified: | 16 Jan 2025 01:46 |
| URI: | http://eprints.um.edu.my/id/eprint/46888 |
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