A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Using Data Mining for Prioritizing Roof Rehabilitation Works
Roofing systems require frequent inspection and rehabilitation due to their continuous exposure to the elements. For large owners who manage many buildings, the low resolution of inspection data leaves many roofs being classified at critical condition. This makes the allocation of the limited rehabilitation funds a very challenging task. To help identify top priority roofs, this study uses clustering techniques to offer a more granular classification of roofing criticality. Clustering is a data mining technique that can group datapoints into distinct clusters of similar attributes. The study uses inspection data from 400 roofs collected from the Toronto District School Board and compares the clustering results of various techniques in terms of roofing severity levels. Based on the study results, the K-Means algorithm has been determined to be most useful. This study is expandable to other asset types and contributes to improving the efficiency of the fund allocation process.
Using Data Mining for Prioritizing Roof Rehabilitation Works
Roofing systems require frequent inspection and rehabilitation due to their continuous exposure to the elements. For large owners who manage many buildings, the low resolution of inspection data leaves many roofs being classified at critical condition. This makes the allocation of the limited rehabilitation funds a very challenging task. To help identify top priority roofs, this study uses clustering techniques to offer a more granular classification of roofing criticality. Clustering is a data mining technique that can group datapoints into distinct clusters of similar attributes. The study uses inspection data from 400 roofs collected from the Toronto District School Board and compares the clustering results of various techniques in terms of roofing severity levels. Based on the study results, the K-Means algorithm has been determined to be most useful. This study is expandable to other asset types and contributes to improving the efficiency of the fund allocation process.
Using Data Mining for Prioritizing Roof Rehabilitation Works
Lecture Notes in Civil Engineering
Walbridge, Scott (editor) / Nik-Bakht, Mazdak (editor) / Ng, Kelvin Tsun Wai (editor) / Shome, Manas (editor) / Alam, M. Shahria (editor) / el Damatty, Ashraf (editor) / Lovegrove, Gordon (editor) / Mostafa, Kareem (author) / Hegazy, Tarek (author)
Canadian Society of Civil Engineering Annual Conference ; 2021
Proceedings of the Canadian Society of Civil Engineering Annual Conference 2021 ; Chapter: 32 ; 423-430
2022-05-30
8 pages
Article/Chapter (Book)
Electronic Resource
English
Using Data Mining for Prioritizing Roof Rehabilitation Works
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