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Bayesian网的信息熵

用信息熵的观点 ,如果将Bayesian网看作Agent的背景知识 ,采用与Bayesian网对应  (本文共4页) 阅读全文>>

吉林大学
吉林大学

贝叶斯网络应用基础研究

贝叶斯网络是用来表示变量之间连接概率的图形模式,提供了一种自然的表示因果关系的方法,具备概率推理能力强、语义清晰、易于理解等特点,是目前不确定知识表示和推理领域中最有效的理论模型之一,也是近年来数据挖掘领域中的研究热点之一。本文在全面地介绍了数据挖掘的历史、贝叶斯网络的发展过程和研究现状、贝叶斯网络分类器、贝叶斯网络的应用基础上,进行了连续变量的贝叶斯网络结构学习,贝叶斯网络分类的研究,数据挖掘结果可视化的研究,贝叶斯网络应用的研究。研究的具体内容包括:(1)通过对连续随机变量之间预测能力及其计算方法的讨论,提出了基于预测能力的连续贝叶斯网络结构学习方法;(2)将遗传算法的思想引入贝叶斯网络分类器的构建,提出了一种基于遗传算法的受限制贝叶斯网络分类器算法;(3)为了限制了贝叶斯网络结构的复杂度,提出了一种多模块集成式贝叶斯网络分类器;(4)贝叶斯分类器在医学图像分析系统中的具体应用;(5)用来处理尿沉渣检查图像中微粒的识别,结果...  (本文共140页) 本文目录 | 阅读全文>>

《信号处理》2020年05期
信号处理

均匀先验分布Bayesian自适应波束形成方法

针对UUV舷侧阵存在观测信号波达方向估计结果有误差的情况,提出了基于均匀先验分布的Bayesian自适应波束形成方法(UB)。该方法假设期望信号的到达方向是区间内服从均匀先验分布的一个变量,利用含有均匀先验...  (本文共6页) 阅读全文>>

《Journal of Systems Engineering and Electronics》2020年03期
Journal of Systems Engineering and Electronics

Bayesian inference for ammunition demand based on Gompertz distribution

Aiming at the problem that the consumption data of new ammunition is less and the demand is difficult to predict,combined with the law of ammunition consumption under different damage grades, a Bayesian inference method for ammunition demand based on Gompertz distribution is proposed. The Bayesian inference model based on Gompertz distribution is constructed,and the system contribution degree is intr...  (本文共11页) 阅读全文>>

《IEEE/CAA Journal of Automatica Sinica》2020年05期
IEEE/CAA Journal of Automatica Sinica

Variational Inference Based Kernel Dynamic Bayesian Networks for Construction of Prediction Intervals for Industrial Time Series With Incomplete Input

Prediction intervals(PIs) for industrial time series can provide useful guidance for workers. Given that the failure of industrial sensors may cause the missing point in inputs, the existing kernel dynamic Bayesian networks(KDBN), serving as an effective method for PIs construction, suffer from high computational load using the stochastic algorithm for inference.This study proposes a variational inference method for ...  (本文共9页) 阅读全文>>

《Nuclear Science and Techniques》2020年08期
Nuclear Science and Techniques

Fault prediction method for nuclear power machinery based on Bayesian PPCA recurrent neural network model

Early fault warning for nuclear power machinery is conducive to timely troubleshooting and reductions in safety risks and unnecessary costs. This paper presents a novel intelligent fault prediction method, integrated probabilistic principal component analysis(PPCA), multi-resolution wavelet analysis, Bayesian inference, and RNN model for nuclear power machinery that consider data uncertainty and chaotic time series. ...  (本文共11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>>