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http://dx.doi.org/10.12652/Ksce.2017.37.6.0949

A Study on Real-Time Operation Method of Urban Drainage System using Data-Driven Estimation  

Son, Ahlong (Disaster Information Research Division, National Disaster Management Research Institute)
Kim, Byunghyun (National Civil Defense and Disaster Management Training Institute, Ministry of the Interior and Safety)
Han, Kunyeun (Kyungpook National University)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.37, no.6, 2017 , pp. 949-963 More about this Journal
Abstract
This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.
Keywords
Drainage pump station; GeoANFIS; Penalty type of genetic algorithm; Operation rule;
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Times Cited By KSCI : 1  (Citation Analysis)
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