Issue |
ITM Web Conf.
Volume 45, 2022
2021 3rd International Conference on Computer Science Communication and Network Security (CSCNS2021)
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Article Number | 01012 | |
Number of page(s) | 11 | |
Section | Computer Technology and System Design | |
DOI | https://doi.org/10.1051/itmconf/20224501012 | |
Published online | 19 May 2022 |
Bayesian network variable elimination method optimal elimination order construction
Naval Logistics Acadbmy, Tianjin 300450, China
* Corresponding author: 1419863531@qq.com
Variable Elimination (VE) is the most basic one of many Bayesian network inference algorithms. The speed and complexity of reasoning mainly depend on the order of elimination. Finding the optimal elimination order is a Nondeterministic Polynomial Hard (NP-Hard) problem, which is often solved by heuristic search in practice. In order to improve the speed of reasoning of the variable elimination method, the minimum, maximum potential, minimum missing edge and minimum added complexity search methods are studied. The Asian network is taken as an example to analyze and calculate the complexity and elimination of the above search method. Meta-order, through MATLAB R2018a, the above different search methods were constructed and reasoned separately. Finally, the performance of the four search methods was compared by inference time analysis. The experimental results show that the minimum increase complexity search method is better than other search methods, and the average time consuming is at least 0.012s, which can speed up the reasoning process of Bayesian network.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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