Optimizing Collective Building Management Through a Machine Learning-Based Decision Support System
| dc.contributor.author | Guvencli,M. | |
| dc.contributor.author | Kiran,H. | |
| dc.contributor.author | Dogan,E. | |
| dc.contributor.author | Dag,H. | |
| dc.contributor.author | Ozyuruyen,B. | |
| dc.contributor.author | Cakar,T. | |
| dc.contributor.other | Management Information Systems | |
| dc.contributor.other | 03. Faculty of Economics, Administrative and Social Sciences | |
| dc.contributor.other | 01. Kadir Has University | |
| dc.date.accessioned | 2024-06-23T21:39:20Z | |
| dc.date.available | 2024-06-23T21:39:20Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This study presents the design, implementation, and evaluation of a Decision Support System (DSS) developed for Collective Building Management. Given the potential advantages of machine learning techniques in this domain, the research explores how these techniques can be used to improve collective building management. The dataset consists of 824,932 records and 15 attributes, after preprocessing the data to fill in missing values with the median. The random forest algorithm was chosen for model training and achieved a performance rate of 71.2%. This model can be used to optimize decision processes in collective building management. The proposed prototype is notable for its ability to automatically generate operational plans. In conclusion, machine learning-based DSSs are effective tools for collective building management. © 2023 IEEE. | en_US |
| dc.identifier.citationcount | 0 | |
| dc.identifier.doi | 10.1109/IISEC59749.2023.10391049 | |
| dc.identifier.isbn | 979-835031803-6 | |
| dc.identifier.scopus | 2-s2.0-85184656384 | |
| dc.identifier.uri | https://doi.org/10.1109/IISEC59749.2023.10391049 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12469/5858 | |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | 4th International Informatics and Software Engineering Conference - Symposium Program, IISEC 2023 -- 4th International Informatics and Software Engineering Conference, IISEC 2023 -- 21 December 2023 through 22 December 2023 -- Ankara -- 196814 | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Collective Building Management | en_US |
| dc.subject | Data Preprocessing | en_US |
| dc.subject | Decision Support System (DSS) | en_US |
| dc.subject | Operational Plan Automation | en_US |
| dc.subject | Random Forest Algorithm | en_US |
| dc.title | Optimizing Collective Building Management Through a Machine Learning-Based Decision Support System | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Dağ, Hasan | |
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| gdc.description.department | Kadir Has University | en_US |
| gdc.description.departmenttemp | Guvencli M., Apsiyon Informatics Sys. Inc., Software-Team Lead, Istanbul, Turkey; Kiran H., Apsiyon Informatics Sys. Inc., Product-Team Lead, Istanbul, Turkey; Dogan E., Apsiyon Informatics Sys. Inc., Software-Management, CPO, Istanbul, Turkey; Dag H., Kadir Has University, Informatics Management Systems, Istanbul, Turkey; Ozyuruyen B., Apsiyon Informatics Sys. Inc., R and D and Innovation Incentives Sen. Sp., Istanbul, Turkey; Cakar T., MEF University, Computer Engineering, Istanbul, Turkey | en_US |
| gdc.description.endpage | 4 | |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 1 | |
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