Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/5274
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Özer Yaman, Gamze | en_US |
dc.contributor.author | Oral, Murat | en_US |
dc.contributor.author | Dinçer, Kevser | en_US |
dc.contributor.author | Canan, Fatih | en_US |
dc.date.accessioned | 2024-03-25T06:48:11Z | - |
dc.date.available | 2024-03-25T06:48:11Z | - |
dc.date.issued | 2023 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/5274 | - |
dc.description.abstract | In this study, it is aimed to present a model in which measures can be taken to improve the energy performance of buildings while designing industrial areas. Within the context of the study, it was investigated in the workplace buildings in the Eski Industry and Karatay Industry in Konya. As a result of the research conducted in the workplaces in the area, 128 different building alternatives emerged in terms of design parameters such as building size, orientation, and exterior wall material properties. Annual heating energy needs of these alternatives are calculated by the calculation method in TSE 825. A fuzzy logic (FL) model, an artificial intelligence method, was created by using some of the calculated values. The rest of the calculated heating energy need values and the values obtained from the FL model were compared with the multiple coefficients of determination (R-squared). As a result of the comparison, it was revealed that the FL model created predicted the annual heating energy need of the buildings by 98.1%. This shows that the FL model created can be used to estimate the annual heating energy need at an accuracy rate of 98.1% of the single volume industrial buildings to be designed. | en_US |
dc.language.iso | en | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Building Energy Performance | en_US |
dc.subject | Fuzzy Logic | en_US |
dc.subject | Architecture and Artificial Intelligence | en_US |
dc.subject | Industrial Buildings | en_US |
dc.subject | Architecture and Machine Learning | en_US |
dc.title | Rule-Based Mamdani- Type Fuzzy Modelling of Buildings Annual Heating Energy Need in Design of Industrial Buildings in KonyaTurkey | en_US |
dc.type | Article | en_US |
dc.relation.conference | Online Journal of Art and Design | en_US |
dc.relation.publication | Online Journal of Art and Design | en_US |
dc.contributor.affiliation | Fakülteler, Mimarlık ve Tasarım Fakültesi, Mimarlık Bölümü | en_US |
dc.relation.issn | 2301-2501 | en_US |
dc.description.volume | 11 | en_US |
dc.description.issue | 4 | en_US |
dc.description.startpage | 332 | en_US |
dc.description.endpage | 353 | en_US |
dc.department | Fakülteler, Mimarlık ve Tasarım Fakültesi, İç Mimarlık Bölümü | en_US |
dc.authorid | 0000-0003-4848-5417 | en_US |
dc.authorid | 0000-0003-4469-1993 | en_US |
dc.institutionauthor | Oral, Murat | en_US |
dc.institutionauthor | Canan, Fatih | en_US |
dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | Article | - |
crisitem.author.dept | 04.02. Department of Interior Architecture | - |
crisitem.author.dept | 02.10. Department of Mechanical Engineering | - |
crisitem.author.dept | 04.01. Department of Architecture | - |
Appears in Collections: | Mimarlık ve Tasarım Fakültesi Koleksiyonu |
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.