Water Environment Risk Prediction Using Bayesian network

Authors

Ershad Sharifahmadian, University of Nevada, Las Vegas
Shahram Latifi, University of Nevada, Las VegasFollow

Document Type

Conference Proceeding

Publication Date

4-4-2013

Publication Title

Conference Proceedings - IEEE SOUTHEASTCON

Publisher

IEEE

First page number:

1

Last page number:

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

Autoregressive processes; Bayes methods; Mathematical model; Maximum likelihood estimation; Predictive models; Probabilistic logic; Water resources

Disciplines

Controls and Control Theory | Electrical and Computer Engineering | Electrical and Electronics | Power and Energy | Signal Processing | Systems and Communications

Language

English

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

Repository Citation

Sharifahmadian, E., Latifi, S. (2013). Water Environment Risk Prediction Using Bayesian network. Conference Proceedings - IEEE SOUTHEASTCON 1-5. IEEE.