Journal Article10.1016/J.KNOSYS.2018.03.007
Novel binary encoding water cycle algorithm for solving Bayesian network structures learning problem
Jingyun Wang,Sanyang Liu +1 more
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TL;DR: A novel binary encoding water cycle algorithm is proposed for the first time to address the Bayesian network structures learning problem and performs well and turns out to have the better solution quality.
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Abstract: Constructing Bayesian network structures from data is a computationally hard task. One important method to learn Bayesian network structures uses the meta-heuristic algorithms. In this paper, a novel binary encoding water cycle algorithm is proposed for the first time to address the Bayesian network structures learning problem. In this study, the sea, rivers and streams correspond to the candidate Bayesian network structures. Since it is a discrete problem to find an optimal structure, the logic operators have been used to calculate the positions of the individuals. Meanwhile, to balance the exploitation and exploration abilities of the algorithm, the ways how rivers and streams flow to the sea and the evaporation process have been designed with the new strategies. Experiments on well-known benchmark networks demonstrate that the proposed algorithm is capable of identifying the optimal or near-optimal structures. In the comparison to the use of the other algorithms, our method performs well and turns out to have the better solution quality.
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Citations
A discrete water cycle algorithm for solving the symmetric and asymmetric traveling salesman problem
Eneko Osaba,Javier Del Ser,Javier Del Ser,Ali Sadollah,Ali Sadollah,Miren Nekane Bilbao,David Camacho +6 more
TL;DR: It is concluded that the proposed DWCA approach outperforms – with statistical significance – any other optimization technique in the benchmark in terms of both computation metrics.
121
Parallel Simulated Annealing with a Greedy Algorithm for Bayesian Network Structure Learning
Sangmin Lee,Seoung Bum Kim +1 more
TL;DR: This work presents a hybrid algorithm called parallel simulated annealing with a greedy algorithm (PSAGA) to learn Bayesian network structures and demonstrates that the proposed PSAGA shows better performance than the alternatives in terms of computational time and accuracy.
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A comprehensive review on water cycle algorithm and its applications
TL;DR: A comprehensive and exhaustive review has been carried out on water cycle algorithm (WCA) and its applications in a wide variety of study fields and can be an innovative and comprehensive reference for subsequent academic papers and books relevant to the WCA, optimization methods, and metaheuristic optimization algorithms.
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An analytical threshold for combining Bayesian Networks
Tadeu Junior Gross,Michel Bessani,Willian Darwin Junior,Renata Bezerra Araujo,Francisco Assis Carvalho Vale,Carlos Dias Maciel +5 more
TL;DR: The resulting BN from the analytical cutoff-frequency captured the expected associations among nodes and also achieved better prediction performance than the BNs learned with neighbours thresholds to the computed.
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Evaluation of Bayesian Network Structure Learning Using Elephant Swarm Water Search Algorithm
Shahab Wahhab Kareem,Mehmet Cudi Okur +1 more
- 01 Jan 2020
TL;DR: The authors present the Elephant Swarm Water Search Algorithm (ESWSA) for Bayesian network structure learning which achieves better performance than the other algorithms and produces better scores as well as the better values.
23
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