基于智能算法的面向目标Credal 网络近似推理方法研究

Approximate Inferring Approach of Goal-Oriented Credal Network Based on Intelligent Algorithms

  • 摘要: 针对大规模Credal网络的推理问题,提出了面向目标分别与遗传算法、蚁群算法、遗传-蚁群算法相结合的智能化近似推理方法. 对这些推理方法进行了设计、实现和比较. 结果表明:智能化近似推理方法获取最优解的效率较高,给决策人员提供影响查询变量特定状态极值概率的敏感Credal集,用于决定对极值决策的信任程度.

     

    Abstract: New inferring methods of goal-oriented Credal networks are proposed such as based on genetic algorithms, Ant colony optimization algorithms and genetic-ant colony optimization algorithms are proposed for the large-scale Credal networks. Through designing, realizing and analysing these inferring methods, it is proved that these inferring methods can not only effectively obtain the best solution, but also can provide sensitive Credal sets of some variables influencing that specify status of goal variable for decision-makers in order to acquire the belief on the extreme decision.

     

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