Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Real-world applications of Bayesian networks
Communications of the ACM
Expert Systems and Probabiistic Network Models
Expert Systems and Probabiistic Network Models
A Guide to the Literature on Learning Probabilistic Networks from Data
IEEE Transactions on Knowledge and Data Engineering
Bayesian networks in planning a large aquifer in Eastern Mancha, Spain
Environmental Modelling & Software
Coupling real-time control and socio-economic issues in participatory river basin planning
Environmental Modelling & Software
Public participation modelling using Bayesian networks in management of groundwater contamination
Environmental Modelling & Software
Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
Environmental Modelling & Software
Reforestation planning using Bayesian networks
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Position Paper: Modelling with stakeholders
Environmental Modelling & Software
Environmental Modelling & Software
Review: Bayesian networks in environmental modelling
Environmental Modelling & Software
Environmental Modelling & Software
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Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83-102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.