Indoor air quality control using backpropagated neural networks

Air conditioning; Air quality; Backpropagation; Indoor air pollution; Neural networks; Proportional control systems; Quality control; Two term control systems; Ventilation; Air quality control; Back-propagated neural networks; Back-propagation neural networks; Fast response; Indoor air; Indoor air q...

Full description

Saved in:
Bibliographic Details
Main Authors: Uskenbayeva R., Altayeva A., Gusmanova F., Abdulkarimova G., Berkimbaeva S., Dalbekova K., Suiman A., Zhanseitova A., Amreyeva A.
Other Authors: 55623134100
Format: Article
Published: Tech Science Press 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Tenaga Nasional
id my.uniten.dspace-27304
record_format dspace
spelling my.uniten.dspace-273042023-05-29T17:42:25Z Indoor air quality control using backpropagated neural networks Uskenbayeva R. Altayeva A. Gusmanova F. Abdulkarimova G. Berkimbaeva S. Dalbekova K. Suiman A. Zhanseitova A. Amreyeva A. 55623134100 56128042000 57207999955 57207999329 57209039051 57223432492 57279137800 57279351800 57279137900 Air conditioning; Air quality; Backpropagation; Indoor air pollution; Neural networks; Proportional control systems; Quality control; Two term control systems; Ventilation; Air quality control; Back-propagated neural networks; Back-propagation neural networks; Fast response; Indoor air; Indoor air quality; Math model; PID; Proportional integral derivatives; Residential construction; Controllers Providing comfortable indoor air quality control in residential construction is an exceedingly important issue. This is due to the structure of the fast response controller of air quality. The presented work shows the breakdown and creation of a mathematical model for an interactive, nonlinear system for the required comfortable air quality. Furthermore, the paper refers to designing traditional proportional integral derivative regulators and proportional, integral, derivative regulators with independent parameters based on a backpropagation neural network. In the end, we perform the experimental outputs of a suggested backpropagation neural network-based proportional, integral, derivative controller and analyze model results by applying the proposed system. The obtained results demonstrated that the proposed controller can provide the required level of clean air in the room. The proposed developed model takes into consideration international Heating, Refrigerating, and air conditioning standards as ASHRAE AND ISO. Based on the findings, we concluded that it is possible to implement a proposed system in homes and offer equivalent indoor air quality with continuous mechanical ventilation without a profuse amount of energy. � 2022 Tech Science Press. All rights reserved. Final 2023-05-29T09:42:25Z 2023-05-29T09:42:25Z 2022 Article 10.32604/cmc.2022.020491 2-s2.0-85116011920 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116011920&doi=10.32604%2fcmc.2022.020491&partnerID=40&md5=09d4448181e88e629e612aa1aece44c2 https://irepository.uniten.edu.my/handle/123456789/27304 70 2 3837 3853 All Open Access, Gold Tech Science Press Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Air conditioning; Air quality; Backpropagation; Indoor air pollution; Neural networks; Proportional control systems; Quality control; Two term control systems; Ventilation; Air quality control; Back-propagated neural networks; Back-propagation neural networks; Fast response; Indoor air; Indoor air quality; Math model; PID; Proportional integral derivatives; Residential construction; Controllers
author2 55623134100
author_facet 55623134100
Uskenbayeva R.
Altayeva A.
Gusmanova F.
Abdulkarimova G.
Berkimbaeva S.
Dalbekova K.
Suiman A.
Zhanseitova A.
Amreyeva A.
format Article
author Uskenbayeva R.
Altayeva A.
Gusmanova F.
Abdulkarimova G.
Berkimbaeva S.
Dalbekova K.
Suiman A.
Zhanseitova A.
Amreyeva A.
spellingShingle Uskenbayeva R.
Altayeva A.
Gusmanova F.
Abdulkarimova G.
Berkimbaeva S.
Dalbekova K.
Suiman A.
Zhanseitova A.
Amreyeva A.
Indoor air quality control using backpropagated neural networks
author_sort Uskenbayeva R.
title Indoor air quality control using backpropagated neural networks
title_short Indoor air quality control using backpropagated neural networks
title_full Indoor air quality control using backpropagated neural networks
title_fullStr Indoor air quality control using backpropagated neural networks
title_full_unstemmed Indoor air quality control using backpropagated neural networks
title_sort indoor air quality control using backpropagated neural networks
publisher Tech Science Press
publishDate 2023
_version_ 1806423249080287232