DocumentCode :
624220
Title :
Water environment risk prediction using Bayesian network
Author :
Sharifahmadian, E. ; Latifi, Sara
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Nevada, Las Vegas, NV, USA
fYear :
2013
fDate :
4-7 April 2013
Firstpage :
1
Lastpage :
5
Abstract :
To improve better usage of water resources, risk prediction of water environment is crucial. Here, Bayesian network is applied to perform water environment risk prediction. In proposed approach, two steps are taken to choose the effective parameters in prediction. The proposed method is applied to water environment data in Nevada. Results show that the proposed method is effective for water environment risk prediction, and improvement of utilization of water resources.
Keywords :
belief networks; directed graphs; risk analysis; water resources; Bayesian network; Nevada; directed acyclic graph; water environment risk prediction; water resources; Autoregressive processes; Bayes methods; Mathematical model; Maximum likelihood estimation; Predictive models; Probabilistic logic; Water resources; Bayesian network; Climate change; Directed acyclic graph; Forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Southeastcon, 2013 Proceedings of IEEE
Conference_Location :
Jacksonville, FL
ISSN :
1091-0050
Print_ISBN :
978-1-4799-0052-7
Type :
conf
DOI :
10.1109/SECON.2013.6567437
Filename :
6567437
Link To Document :
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