Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control

Climate control; Climate models; Control systems; Energy utilization; Fuzzy inference; Fuzzy neural networks; Office buildings; Predictive analytics; Comfort temperatures; Commercial building; Hardware and software; Indoor environment; Indoor temperature; Management strategies; Microclimate control;...

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Main Authors: Suliman A., Uskenbayeva R., Altayeva A.
Other Authors: 25825739000
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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author Suliman A.
Uskenbayeva R.
Altayeva A.
author2 25825739000
author_facet 25825739000
Suliman A.
Uskenbayeva R.
Altayeva A.
author_sort Suliman A.
building UNITEN Library
collection Institutional Repository
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
continent Asia
country Malaysia
description Climate control; Climate models; Control systems; Energy utilization; Fuzzy inference; Fuzzy neural networks; Office buildings; Predictive analytics; Comfort temperatures; Commercial building; Hardware and software; Indoor environment; Indoor temperature; Management strategies; Microclimate control; Neuro-Fuzzy model; HVAC
format Conference Paper
id my.uniten.dspace-25305
institution Universiti Tenaga Nasional
publishDate 2023
publisher Institute of Electrical and Electronics Engineers Inc.
record_format dspace
spelling my.uniten.dspace-253052023-05-29T16:08:00Z Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control Suliman A. Uskenbayeva R. Altayeva A. 25825739000 55623134100 56128042000 Climate control; Climate models; Control systems; Energy utilization; Fuzzy inference; Fuzzy neural networks; Office buildings; Predictive analytics; Comfort temperatures; Commercial building; Hardware and software; Indoor environment; Indoor temperature; Management strategies; Microclimate control; Neuro-Fuzzy model; HVAC This paper proposes a concept for managing climate control systems (HVAC systems) in large commercial buildings based on predictive models. The proposed control concept reduces the consumption of gas used for room heating while maintaining the acceptable range of the required temperature. The authors propose fuzzy and neuro-fuzzy models to ensure comfort temperature and humidity in the indoor environment, and thus minimize energy consumption. The management strategy is formed using predictive models. The developed management strategy is applied to the climate control system through a hardware and software complex consisting of a client connected to the system and a server that forecasts changes in indoor temperature, gas consumption and forms a management strategy. The tests that implemented the proposed concept were performed in a commercial building. The efficiency of the proposed concept is shown in comparison with the control algorithm built into the HVAC system. � 2020 IEEE. Final 2023-05-29T08:08:00Z 2023-05-29T08:08:00Z 2020 Conference Paper 10.1109/ICIMU49871.2020.9243606 2-s2.0-85097651874 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097651874&doi=10.1109%2fICIMU49871.2020.9243606&partnerID=40&md5=092d348066b9c0a795f847699ba49ce1 https://irepository.uniten.edu.my/handle/123456789/25305 9243606 177 182 Institute of Electrical and Electronics Engineers Inc. Scopus
spellingShingle Suliman A.
Uskenbayeva R.
Altayeva A.
Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
title Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
title_full Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
title_fullStr Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
title_full_unstemmed Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
title_short Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control
title_sort applying neuro-fuzzy model in indoor comfort microclimate control
url_provider http://dspace.uniten.edu.my/