On Approximating K-MPE of Bayesian Networks Using Genetic Algorithm

N. Sriwachirawat, S. Auwatanamongkol
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引用次数: 7

Abstract

This paper presents a new genetic algorithm that efficiently finds k-MPE of Bayesian networks. The algorithm is based on niching method and is designed to utilize multifractral characteristic and clustering property of Bayesian networks to improve a search toward solutions. Benchmark tests are performed to evaluate the effectiveness of the algorithm and compare its performance with other niching genetic algorithms. The results from the tests show that the new algorithm outperforms the others for both running time and accuracy
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用遗传算法逼近贝叶斯网络的K-MPE
本文提出了一种新的遗传算法,可以有效地找到贝叶斯网络的k-MPE。该算法基于小生境方法,旨在利用贝叶斯网络的多重分形特征和聚类特性来提高对解的搜索速度。通过基准测试来评估算法的有效性,并将其与其他小生境遗传算法的性能进行比较。测试结果表明,新算法在运行时间和精度上都优于其他算法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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