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基于进化算法的Bayesian网结构学习研究

Bayesian网是联合概率分布的图形表示方式,目前已成为人工智能领域中不确定问题处理的一种强有力工具。仅由人类专家建造Bayesian网是困难的,从数据中学习Bayesian网已成为近年来十分活跃的研究领域。本文提出了两种基于进化算法的Bayesian网结构学习算法。一种是基于(μ,λ)-ES进化策略的Bayesian网结构增量学习算法。该算法可以在没有旧数据的情况下,完全通过上一次学习所得出的Bayesian网及新获得的训练数据进行增量学习,克服了目前多数算法需要保存旧数据的缺点,节省了存储空间。本文还提出了一种具有较小搜索空间的Bayesian网结构学习算法,首先使用蚁群算法对变量的顺序进行学习。然后在最优变量顺序下,利用遗传算法对结构进行学习,算法中使用一种新的编码方式,使进化过程中不会产生含有环的非法结构。该算法的搜索空间小于目前多数算法的搜索空间。实验结果表明,本文提出的两种算法能有效的进行Bayesian网结构学习  (本文共77页) 本文目录 | 阅读全文>>

《吉林大学学报(理学版)》2006年06期
吉林大学学报(理学版)

基于免疫进化算法的Bayesian网结构学习

利用免疫进化算法(IEA),借助遗传和接种疫苗操作将基于打分和基于约束的两类Bayesian网结构学习方法有机地结合在一起,提出一种新的Ba...  (本文共6页) 阅读全文>>

《China Ocean Engineering》2019年01期
China Ocean Engineering

Failure Statistics Analysis Based on Bayesian Theory: A Study of FPSO Internal Turret Leakage

The load and corrosion caused by the harsh marine environment lead to the severe degradation of offshore equipment and to their compromised security and reliability. In the quantitative risk analysis, the failure models are difficult to establish through traditional statistical methods. Hence, the calculation of the occurrence probability of small sample events is often met with great uncertainty. In this study, the ...  (本文共12页) 阅读全文>>

《Big Data Mining and Analytics》2019年03期
Big Data Mining and Analytics

Bayesian Analysis of Complex Mutations in HBV, HCV,and HIV Studies

In this article, we aim to provide a thorough review of the Bayesian-inference-based methods applied to Hepatitis B Virus(HBV), Hepatitis C Virus(HCV), and Human Immunodeficiency Virus(HIV) studies with a focus on the detection of the viral mutations and various problems which are correlated to these mutations. It is particularly difficult to detect and interpret these interacting mutation patterns, but by using Baye...  (本文共14页) 阅读全文>>

《Journal of Electronic Science and Technology》2019年01期
Journal of Electronic Science and Technology

Hyperparameter Optimization for Machine Learning Models Based on Bayesian Optimization

Hyperparameters are important for machine learning algorithms since they directly control the behaviors of training algorithms and have a significant effect on the performance of machine learning models. Several techniques have been developed and successfully applied for certain application domains. However, this work demands professional knowledge and expert experience. And sometimes it has to resort to the brute-fo...  (本文共15页) 阅读全文>>

《Communications in Theoretical Physics》2019年09期
Communications in Theoretical Physics

Comparison Between χ~2 and Bayesian Statistics with Considering the Redshift Dependence of Stretch and Color from JLA Data

In this work, we compare the impacts given by χ~2 statistics and Bayesian statistics. Bayesian statistics is a new statistical method proposed by [C. Ma, P. S. Corasaniti, and B. A. Bassett, arXiv:1603.08519[astro-ph.CO](2016)]recently, which gives a fully account for the standard-candle parameter dependence of the data covariance matrix. For this two statistical methods, we explore the possible redshift-dependence o...  (本文共12页) 阅读全文>>

《Acta Mathematicae Applicatae Sinica》2018年01期
Acta Mathematicae Applicatae Sinica

Bayesian Planning of Optimal Step-stress Accelerated Life Test for Log-location-scale Distributions

This paper introduces some Bayesian optimal design methods for step-stress accelerated life test planning with one accelerating variable, when the acceleration model is linear in the accelerated variable or its function, based on censored data from a log-location-scale distributions. In order to find the optimal plan,we propose different...  (本文共14页) 阅读全文>>