南京大学学报（自然科学版）2024，Vol.60Issue(3)：396-405,10.DOI:10.13232/j.cnki.jnju.2024.03.004
基于遗传算法联姻策略的贝叶斯网络结构学习
Bayesian network structure learning method based on genetic algorithm marriage strategy
摘要
Abstract
The study of Bayesian network structure based on evolution methods suffers from local optimality and low efficiency.To address this issure,a Bayesian network structure learning method based on genetic algorithm marriage strategy is proposed.First of all,the"same"marriage strategy is designed.That is,two groups use the same search strategy and evaluate models to complete the Bayesian network structure learning.Then we marry the best quality sub-generation individuals,and iterate the best quality sub-generation individuals.Because the sub-generation of the marriage retains another group of segments,it has a good guarantee for the diversity of genes in the population,and effectively avoids the defects caused by the reproduction of close relatives.In response to the marriage strategy of the same agent model failing to ensure the quality of network structure and learning efficiency at the same time,we propose integrated genetic algorithm marriage strategies.Specifically,two groups use different agency models and search strategies to learn,and then the best-quality individuals in each group are married and iterated.Experiments show that the learning accuracy and effectiveness of the proposed algorithm on all-scale networks are better than the comparative algorithm.关键词
遗传算法/联姻策略/代理模型/贝叶斯网络结构Key words
genetic algorithm/marriage strategy/surrogate model/Bayesian network structure分类
信息技术与安全科学引用本文复制引用
朱宇,王慧玲,徐苗,綦小龙..基于遗传算法联姻策略的贝叶斯网络结构学习[J].南京大学学报（自然科学版）,2024,60(3):396-405,10.基金项目
新疆维吾尔自治区自然科学基金(2021D01C467),南京大学计算机软件新技术国家重点实验室项目(KFKT2022B30) （2021D01C467）
