Fusion, propagation, and structuring in belief networks
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in expert systems: theory and algorithms
Probabilistic reasoning in expert systems: theory and algorithms
Fusion and propagation with multiple observations in belief networks
Artificial Intelligence
Real-world applications of Bayesian networks
Communications of the ACM
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Coupling real-time control and socio-economic issues in participatory river basin planning
Environmental Modelling & Software
Editorial: Bayesian networks in water resource modelling and management
Environmental Modelling & Software
Coupling real-time control and socio-economic issues in participatory river basin planning
Environmental Modelling & Software
Environmental Modelling & Software
A general water supply planning model: Evaluation of decentralized treatment
Environmental Modelling & Software
Environmental Modelling & Software
Reforestation planning using Bayesian networks
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Position Paper: Modelling with stakeholders
Environmental Modelling & Software
Adaptive modelling for adaptive water quality management in the Great Barrier Reef region, Australia
Environmental Modelling & Software
An integrated approach to linking economic valuation and catchment modelling
Environmental Modelling & Software
Environmental Modelling & Software
Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network
Environmental Modelling & Software
Analysis of facility location model using Bayesian Networks
Expert Systems with Applications: An International Journal
Review: Bayesian networks in environmental modelling
Environmental Modelling & Software
Position Paper: A general framework for Dynamic Emulation Modelling in environmental problems
Environmental Modelling & Software
Data-driven dynamic emulation modelling for the optimal management of environmental systems
Environmental Modelling & Software
Assessing the likelihood of realizing idealized goals: The case of urban water strategies
Environmental Modelling & Software
Good practice in Bayesian network modelling
Environmental Modelling & Software
Prediction analysis of a wastewater treatment system using a Bayesian network
Environmental Modelling & Software
Model development of a Bayesian Belief Network for managing inundation events for wetland fish
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Environmental Modelling & Software
Hi-index | 0.00 |
Bayesian Networks (Bns) are emerging as a valid approach for modelling and supporting decision making in the field of water resource management. Based on the coupling of an interaction graph to a probabilistic model, they have the potential to improve participation and allow integration with other models. The wide availability of ready-to-use software with which Bn models can be easily designed and implemented on a PC is further contributing to their spread. Although a number of papers are available in which the application of Bns to water-related problems is investigated, the majority of these works use the Bn semantics to model the whole water system, and thus do not discuss their integration with other types of model. In this paper some pros and cons of adopting Bns for water resource planning and management are analyzed by framing their use within the context of a participatory and integrated planning procedure, and exploring how they can be integrated with other types of models.