BNC-PSO: structure learning of Bayesian networks by particle swarm optimization
From MaRDI portal
Publication:1991849
DOI10.1016/j.ins.2016.01.090zbMath1398.68435OpenAlexW2277112320MaRDI QIDQ1991849
Publication date: 30 October 2018
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2016.01.090
particle swarm optimization (PSO)structure learningmutation operationBayesian information criteria (BIC)Bayesian network (BN)cross-over operation
Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)
Related Items
A novel discrete particle swarm optimization algorithm for solving bayesian network structures learning problem ⋮ Mutual-information-inspired heuristics for constraint-based causal structure learning ⋮ Particle swarm optimization-based variable selection in Poisson regression analysis via information complexity-type criteria ⋮ Learning the structure of Bayesian networks with ancestral and/or heuristic partition ⋮ Learning Bayesian networks based on bi-velocity discrete particle swarm optimization with mutation operator ⋮ A decomposition-based algorithm for the double row layout problem ⋮ Multi-period portfolio selection with dynamic risk/expected-return level under fuzzy random uncertainty ⋮ Learning Bayesian network structures using weakest mutual-information-first strategy
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Hierarchical Bayesian optimization algorithm. Toward a new generation of evolutionary algorithms. With a foreword by David E. Goldberg
- The max-min hill-climbing Bayesian network structure learning algorithm
- Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis
- Wrappers for feature subset selection
- A Bayesian method for the induction of probabilistic networks from data
- Estimating the dimension of a model
- Adaptive probabilistic networks with hidden variables
- Ant colony optimization for learning Bayesian networks.
- A new approach for learning belief networks using independence criteria
- Learning Bayesian networks: The combination of knowledge and statistical data
- Characteristic imsets for learning Bayesian network structure
- A review on evolutionary algorithms in Bayesian network learning and inference tasks
- A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
- Bayesian network classifiers versus selective \(k\)-NN classifier
- A novel method for combining Bayesian networks, theoretical analysis, and its applications
- Learning Optimal Bayesian Networks: A Shortest Path Perspective
- A Review of Bayesian Networks and Structure Learning
- A Tutorial on Learning with Bayesian Networks
- Learning Bayesian Network Equivalence Classes with Ant Colony Optimization
- 10.1162/153244302760200696
- A hybrid methodology for learning belief networks: BENEDICT
- A new look at the statistical model identification
This page was built for publication: BNC-PSO: structure learning of Bayesian networks by particle swarm optimization