Design of energy consumption monitoring system of public buildings based on artificial neural network. (27th June 2022)
- Record Type:
- Journal Article
- Title:
- Design of energy consumption monitoring system of public buildings based on artificial neural network. (27th June 2022)
- Main Title:
- Design of energy consumption monitoring system of public buildings based on artificial neural network
- Authors:
- He, Chuan
Lin, Jin
Xiang, Xin
Yu, Lie
Xiong, Hui-hua - Abstract:
- In order to overcome the problems of low monitoring accuracy and long response time in traditional energy consumption monitoring system of public buildings, a new energy consumption monitoring system of public buildings based on artificial neural network is proposed. The system hardware is designed by using the energy consumption collection subsystem and energy consumption data transmission subsystem of public buildings. Through the genetic algorithm to optimise the constraint parameters of the physical sign extraction function to obtain the characteristics of public building energy consumption, combined with the main factors affecting the building energy consumption, the public building energy consumption monitoring model based on artificial neural network is established, and the real-time monitoring of public building energy consumption is realised through the model. The experimental results show that, compared with the traditional monitoring system, the minimum monitoring error of the designed system is only 0.01.
- Is Part Of:
- International journal of industrial and systems engineering. Volume 41:Number 3(2022)
- Journal:
- International journal of industrial and systems engineering
- Issue:
- Volume 41:Number 3(2022)
- Issue Display:
- Volume 41, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 41
- Issue:
- 3
- Issue Sort Value:
- 2022-0041-0003-0000
- Page Start:
- 349
- Page End:
- 362
- Publication Date:
- 2022-06-27
- Subjects:
- artificial neural network -- public building -- energy consumption monitoring system -- genetic algorithm
Systems engineering -- Periodicals
Industrial engineering -- Periodicals
620.001171 - Journal URLs:
- http://www.inderscience.com/browse/index.php?journalCODE=ijise ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 1748-5037
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 21517.xml