The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Learning Bayesian networks from data: an information-theory based approach
Artificial Intelligence
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks
ENC '04 Proceedings of the Fifth Mexican International Conference in Computer Science
Learning Bayesian Networks
Bayesian network learning algorithms using structural restrictions
International Journal of Approximate Reasoning
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Learning Bayesian networks from incomplete databases using a novel evolutionary algorithm
Decision Support Systems
Dealing with Complexity in Large Scale and Structured Fuzzy Systems
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Statistical analysis of simulation output
Proceedings of the 40th Conference on Winter Simulation
Modeling and Reasoning with Bayesian Networks
Modeling and Reasoning with Bayesian Networks
Learning Bayesian network parameters under incomplete data with domain knowledge
Pattern Recognition
Causality: Models, Reasoning and Inference
Causality: Models, Reasoning and Inference
Learning Bayesian network parameters under order constraints
International Journal of Approximate Reasoning
Bayesian network modeling for evolutionary genetic structures
Computers & Mathematics with Applications
A hybrid method for learning Bayesian networks based on ant colony optimization
Applied Soft Computing
Expert Systems with Applications: An International Journal
Good practice in Bayesian network modelling
Environmental Modelling & Software
A proposed validation framework for expert elicited Bayesian Networks
Expert Systems with Applications: An International Journal
| Hi-index | 0.09 |
Bayesian Networks are increasingly being used to model complex socio-economic systems by expert knowledge elicitation even when data is scarce or does not exist. In this paper, a Multi-Objective Evolutionary Algorithm (MOEA) is presented for assessing the parameters (input relevance/weights) of fuzzy dependence relationships in a Bayesian Network (BN). The MOEA was designed to include a hybrid model that combines Monte-Carlo simulation and fuzzy inference. The MOEA-based prototype assesses the input weights of fuzzy dependence relationships by learning from available output data. In socio-economic systems, the determination of how a specific input variable affects the expected results can be critical and it is still one of the most important challenges in Bayesian modeling. The MOEA was checked by estimating the migrant stock as a relevant variable in a BN model for forecasting remittances. For a specific year, results showed similar input weights than those given by economists but it is very computationally demanding. The proposed hybrid-approach is an efficient procedure to estimate output values in BN.