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Basic Study on Urgency Classification Model for Sewage Pipe Using Machine Learning
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1  Kanazawa University
Academic Editor: Wataru Takeuchi

https://doi.org/10.3390/ohow2022-13657 (registering DOI)
Abstract:

The number of aging sewage pipes is on the increase, and Japan is facing three shortages in financial resources, human resources, and technology for maintenance and management. Under these circumstances, it is difficult to conduct equal surveys of the vast number of sewage pipes. Therefore, the development of more efficient and effective inspection methods is required. In this study, as an approach to the realization of efficient management, an urgency classification model for sewage pipes was constructed and evaluated by utilizing the inspection results of sewage pipes.

Keywords: Machine Learning, Sewage Pipe, Inspection Efficiency

 
 
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