2012 Fiscal Year Final Research Report
Evaluation of Infrastructure Facilities Using Machine Learning
| Project/Area Number |
23710185
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Kansai University |
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Principal Investigator |
YUN Yeboon 関西大学, 環境都市工学部, 准教授 (10325326)
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| Project Period (FY) |
2011 – 2012
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| Keywords | 社会システム / 維持管理 |
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| Research Abstract |
In this research，we suggest a method using support vector machines (SVM) to evaluate objectively and effectively sewerage systems．Utilizing the characteristics of SVM，we elicit relevant attributes (factors) to collapse of roads from basic data and inspection for the sewerage systems in which road subsidence has occurred due to damaged sewer pipes．Calculating latent risk degree of each sewerage system，we decide a priority for maintaining preventively，properly and efficiently．Finally，the effectiveness of the proposed method will be investigated through some real inspection data．
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Research Products
(16 results)
