1. Bayesian approach 对于多项式拟合问题,我们可通过最小二乘(least squares)的方式计算得到模型的参数,最小二乘法又可视为最大似然(maximum likelihood)的一种特例,当模型选择过于复杂时,很容易在测试集上造成过拟合(over-fitting),因此,过拟合问题可被理解为最大似然普遍存在的一种性质。 过拟合的问题可通过...
1. Bayesian approach 对于多项式拟合问题,我们可通过最小二乘(least squares)的方式计算得到模型的参数,最小二乘法又可视为最大似然(maximum likelihood)的一种特例,当模型选择过于复杂时,很容易在测试集上造成过拟合(over-fitting),因此,过拟合问题可被理解为最大似然普遍存在的一种性质。 过拟合的问题可通过贝叶...
Bayesian probabilistic approach for model updating and damage detection for a large truss bridge Mustafa, S., Debnath, N., Dutta, A., Bayesian probabilistic approach for model updating and damage detection for a large truss bridge. International ... S Mustafa,Debnath, N,A Dutta - 《...
This paper proposes a probabilistic approach for characterising the static risk of individual ships based on Bayesian networks (BNs). The approach uses the Ship Risk Profile parameters of the New Inspection Regime of the Paris Memorandum of Understanding (MoU) on Port State Control (PSC), not as...
Title PagesPage 1 of 4University Press Scholarship OnlineOxford Scholarship OnlineBayesian Rationality: The probabilistic approach tohuman reasoningMike Oaksford and Nick ChaterPrint publication date: 2007Print ISBN-13: 9780198524496Published to Oxford Scholarship Online: April 2010DOI: 10.1093/acprof:oso/...
A Bayesian probabilistic approach is presented for selecting the most plausible class of models for a structural or mechanical system within some specified... JL Beck,KV Yuen - 《Journal of Engineering Mechanics》 被引量: 525发表: 2004年 Statistical-mechanical approach to image processing The basic...
N. Learning to Estimate Dynamical State with Probabilistic Population Codes. PLoS Computational Biology 11, 1–28 (2015). Article Google Scholar Kalman, R. E. A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME Journal of Basic Engineering 82, 35–45 (1960)....
而后面出现的粒子滤波又将该算法一般化,允许噪声分布为任意形式且状态转移方程也可以非线性。本文主要参考《概率机器人》(Probabilistic-Robotics)[4]和《贝叶斯滤波与平滑》(Bayesian Filtering and Smoothing)[5]等书对该基础的贝叶斯滤波算法进行介绍,后面再继续介绍其衍生的版本,如卡尔曼滤波和粒子滤波。
To give guidance in defining probability distributions for model inputs in probabilistic sensitivity analysis (PSA) from a full Bayesian perspective. Methods A common approach to defining probability distributions for model inputs in PSA on the basis of input-related data is to use the likelihood of...
A Bayesian network (BN) approach is employed to handle the relationships among the indicators. BN is known for its capability of handling causal dependencies between different variables in probabilistic terms. However, the use of BN is limited to static systems that are in a state of equilibrium...