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Identification of a Contaminant Source Location in a River System Using Random Forest Models

Title
Identification of a Contaminant Source Location in a River System Using Random Forest Models
Author
박철진
Keywords
contaminant; sensor network; river system; source identification; random forest
Issue Date
2018-03
Publisher
MDPI
Citation
WATER, v. 10, no. 4, Article no. 391
Abstract
We consider the problem of identifying the source location of a contaminant via analyzing changes in concentration levels observed by a sensor network in a river system. To address this problem, we propose a framework including two main steps: (i) pre-processing data; and (ii) training and testing a classification model. Specifically, we first obtain a data set presenting concentration levels of a contaminant from a simulation model, and extract numerical characteristics from the data set. Then, random forest models are generated and assessed to identify the source location of a contaminant. By using the numerical characteristics from the prior step as their inputs, the models provide outputs representing the possibility, i.e., a value between 0 and 1, of a spill event at each candidate location. The performance of the framework is tested on a part of the Altamaha river system in the state of Georgia, United States of America.
URI
https://www.mdpi.com/2073-4441/10/4/391http://repository.hanyang.ac.kr/handle/20.500.11754/117825
ISSN
2073-4441
DOI
10.3390/w10040391
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > INDUSTRIAL ENGINEERING(산업공학과) > Articles
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