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http://dx.doi.org/10.5391/IJFIS.2007.7.4.279

On-line Diagnosis System with Learning Bayesian Networks for fsEBPR  

Cheon, Seong-Pyo (Department of Electrical Engineering, Pusan National University)
Kim, Sung-Shin (Department of Electrical Engineering, Pusan National University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.7, no.4, 2007 , pp. 279-284 More about this Journal
Abstract
Nowadays, due to development of automatic control devices and various sensors, one operator can freely handle several remote plants and processes. Automatic diagnosis and warning systems have been adopted in various fields, in order to prepare an operator's absence for patrolling plants. In this paper, a Bayesian networks based on-line diagnosis system is proposed for a wastewater treatment process. Especially, the suggested system is included learning structure, which can continuosly update conditional probabilities in the networks. To evaluate performance of proposed model, we made a lab-scale five-stage step-feed enhanced biological phosphorous removal process plant and applied on-line diagnosis system to this plant in the summer.
Keywords
On-line Diagnosis System; Learning Bayesian Networks; fsEBPR Plant;
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