Water environment risk prediction using bayesian network
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.
Autoregressive processes; Bayes methods; Mathematical model; Maximum likelihood estimation; Predictive models; Probabilistic logic; Water resources
Controls and Control Theory | Electrical and Computer Engineering | Electrical and Electronics | Power and Energy | Signal Processing | Systems and Communications
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Water environment risk prediction using bayesian network.
Conference Proceedings - IEEE SOUTHEASTCON