BAYESIAN INFERENCE FOR SOLVING A CLASS OF HEAT CONDUCTION PROBLEMS

被引：4
|
作者：
Lai, Jun-Feng [1 ]
Yan, Zai-Zai [1 ]
He, Ji-Huan [2 ,3 ]
机构：
[1] Inner Mongolia Univ Technol, Sci Coll, Hohhot, Peoples R China
[2] Henan Polytech Univ, Sch Math & Informat Sci, Jiaozuo, Henan, Peoples R China
[3] Soochow Univ, Coll Text & Clothing Engn, Natl Engn Lab Modern Silk, Suzhou, Peoples R China
来源：
THERMAL SCIENCE | 2021年 / 25卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Bayesian inference; heat conduction problem; Markov chain Monte-Carlo; STRONG-CONVERGENCE; DIFFUSION-MODELS; SCHEME;
D O I：
10.2298/TSCI191226098L
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
This paper considers a heat conduction problem of a common continuum-type stochastic mathematical model in an engineering field. The approximate solution is calculated with the Markov chain Monte-Carlo algorithm for the heat conduction problem. Three examples are given to illustrate the solution process of the method.
引用
收藏
页码：2135 / 2142
页数：8
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