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Modeling Deep Neural Networks to Learn Maintenance and Repair Costs of Educational Facilities

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Department of Architectural Engineering, Mokpo National University, Mokpo 58554, Korea
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Department of Civil Engineering, Gangneung-Wonju National University, Gangneung 25457, Korea
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Department of Architectural Engineering, Kyung Hee University, Suwon 17104, Korea
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School of Architectural Engineering, University of Ulsan, Ulsan 44610, Korea
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School of Computing, Engineering and Physical Sciences, University of the West of Scotland, Paisley PA1 2BE, UK
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Author to whom correspondence should be addressed.
Academic Editor: Carlos Oliveira Cruz
Buildings 2021, 11(4), 165; https://doi.org/10.3390/buildings11040165
Received: 28 March 2021 / Revised: 13 April 2021 / Accepted: 14 April 2021 / Published: 15 April 2021
Educational facilities hold a higher degree of uncertainty in predicting maintenance and repair costs than other types of facilities. Moreover, achieving accurate and reliable maintenance and repair costs is essential, yet very little is known about a holistic approach to learning them by incorporating multi-contextual factors that affect maintenance and repair costs. This study fills this knowledge gap by modeling and validating deep neural networks to efficiently and accurately learn maintenance and repair costs, drawing on 1213 high-confidence data points. The developed model learns and generalizes claim payout records on the maintenance and repair costs from sets of facility asset information, geographic profiles, natural hazard records, and other causes of financial losses. The robustness of the developed model was tested and validated by measuring the root mean square error and mean absolute error values. This study attempted to propose an analytical modeling framework that can accurately learn various factors, significantly affecting the maintenance and repair costs of educational facilities. The proposed approach can contribute to the existing body of knowledge, serving as a reference for the facilities management of other functional types of facilities. View Full-Text
Keywords: educational facilities; deep learning; deep neural network; maintenance and repair cost; facilities management educational facilities; deep learning; deep neural network; maintenance and repair cost; facilities management
MDPI and ACS Style

Kim, J.; Yum, S.; Son, S.; Son, K.; Bae, J. Modeling Deep Neural Networks to Learn Maintenance and Repair Costs of Educational Facilities. Buildings 2021, 11, 165. https://doi.org/10.3390/buildings11040165

AMA Style

Kim J, Yum S, Son S, Son K, Bae J. Modeling Deep Neural Networks to Learn Maintenance and Repair Costs of Educational Facilities. Buildings. 2021; 11(4):165. https://doi.org/10.3390/buildings11040165

Chicago/Turabian Style

Kim, Jimyong, Sangguk Yum, Seunghyun Son, Kiyoung Son, and Junseo Bae. 2021. "Modeling Deep Neural Networks to Learn Maintenance and Repair Costs of Educational Facilities" Buildings 11, no. 4: 165. https://doi.org/10.3390/buildings11040165

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