Publication:
Applying Neuro-Fuzzy Model in Indoor Comfort Microclimate Control

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dc.citedby1
dc.contributor.authorSuliman A.en_US
dc.contributor.authorUskenbayeva R.en_US
dc.contributor.authorAltayeva A.en_US
dc.contributor.authorid25825739000en_US
dc.contributor.authorid55623134100en_US
dc.contributor.authorid56128042000en_US
dc.date.accessioned2023-05-29T08:08:00Z
dc.date.available2023-05-29T08:08:00Z
dc.date.issued2020
dc.descriptionClimate 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; HVACen_US
dc.description.abstractThis 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9243606
dc.identifier.doi10.1109/ICIMU49871.2020.9243606
dc.identifier.epage182
dc.identifier.scopus2-s2.0-85097651874
dc.identifier.spage177
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097651874&doi=10.1109%2fICIMU49871.2020.9243606&partnerID=40&md5=092d348066b9c0a795f847699ba49ce1
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25305
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2020 8th International Conference on Information Technology and Multimedia, ICIMU 2020
dc.titleApplying Neuro-Fuzzy Model in Indoor Comfort Microclimate Controlen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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