刘浩然^{1, 2,,},
王念太^{1, 2},
王毅^{1, 2},
张力悦^{1, 2},
苏昭玉^{1, 2},
刘文³,
赵旭丹³
1.燕山大学信息科学与工程学院 秦皇岛 066004
2.河北省特种光纤与光纤传感重点实验室 秦皇岛 066004
3.北京市机电研究院 北京 100027
基金项目:国家重点研发计划(2019YFB1707301)，河北省人才工程培养资助项目(A201903005)

详细信息

作者简介:刘浩然：男，1980年生，教授，博士生导师，研究方向为无线传感器网络、工业故障检测及预测
王念太：男，1996年生，硕士生，研究方向为贝叶斯网络、工业故障检测及预测
王毅：男，1996年生，硕士生，研究方向为贝叶斯网络、工业故障检测及预测
张力悦：男，1994年生，博士生，研究方向为贝叶斯网络、工业故障检测及预测
苏昭玉：女，1994年生，硕士生，研究方向为贝叶斯网络、工业故障检测及预测
刘文：女，1966年生，学士，研究方向为机床工艺参数感知与预测
赵旭丹：女，1981年生，硕士，研究方向为财务会计理论与方法

通讯作者:刘浩然　liu.haoran@ysu.edu.cn

中图分类号:TP18

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文章访问数:292
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被引次数:0

出版历程

收稿日期:2021-01-11
修回日期:2021-04-21
网络出版日期:2021-05-07
刊出日期:2021-11-23

Bayesian Network Structure Algorithm Based on V-structure & Log-Likelihood Orientation and Tabu Hill Climbing

Haoran LIU^{1, 2,,},
Niantai WANG^{1, 2},
Yi WANG^{1, 2},
Liyue ZHANG^{1, 2},
Zhaoyu SU^{1, 2},
Wen LIU³,
Xudan ZHAO³
1. School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China
2. The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, Yanshan University, Qinhuangdao 066004, China
3. Beijing Institute of Mechanical and Electrical Engineering, Beijing 100027, China
Funds:The National Key R&D Program of China (2019YFB1707301), The Hebei Talent Engineering Training Support Project (A201903005)


摘要
摘要:针对爬山算法搜索空间过大和易陷入局部最优的问题，该文提出基于V-结构&对数似然函数定向与禁忌爬山的贝叶斯网络结构算法(VTH)。该算法利用定向最大支撑树约束搜索空间，在最大支撑树定向过程中，提出V-结构与对数似然函数(VLL)结合的定向策略；在评分搜索过程中，提出禁忌爬山(VTH)评分搜索策略，该策略将禁忌表清空机制与爬山搜索的局部择优准则结合，在提高全局寻优能力的同时也能保证搜索效率。该算法与其他算法在Asia, Car, Child和Alarm 4种标准网络中进行仿真实验，对比汉明距离、F1值、平衡评分函数(BSF)值、运行时间4个指标，验证了该算法的有效性。
关键词:贝叶斯网络结构/
爬山算法/
禁忌搜索/
定向最大支撑树
Abstract:Hill climbing algorithm has too large search space and is easy to fall into local optimum. In this paper, a new Bayesian network structure algorithm based on V-structure & log-likelihood orientation and Tabu Hill (VTH) climbing is proposed. The algorithm limits the search space by using the oriented maximum weight spanning tree. In the process of maximum weight spanning tree orientation, the orientation strategy based on V-structure and Log-Likelihood (VLL) function is proposed. Tabu Hill Climbing (THC) scoring search strategy is established during the process of search, it combines the tabu list clearing mechanism with the local optimization criteria of hill climbing, the strategy not only ensures the search efficiency, but also improves the global optimization ability. By comparing Hamming distance, F1-value, Balanced Scoring Function(BSF) value and Time with other algorithms in Asia, Car, Child and Alarm standard networks, the effectiveness of the proposed algorithm is verified.
Key words:Bayesian network structure/
Hill climbing algorithm/
Tabu search/
Oriented maximum weight spanning tree



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