The First Exit Time Stochastic Theory Applied to Estimate the Life-Time of a Complicated System
被引:0
作者:
Christos H. Skiadas
论文数: 0引用数: 0
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机构:Technical University of Crete,ManLab
Christos H. Skiadas
Charilaos Skiadas
论文数: 0引用数: 0
h-index: 0
机构:Technical University of Crete,ManLab
Charilaos Skiadas
机构:
[1] Technical University of Crete,ManLab
[2] Hanover College,Department of Mathematics and Computer Science
来源:
Methodology and Computing in Applied Probability
|
2020年
/
22卷
关键词:
Hitting time;
First exit time;
Inverse Gaussian;
Extended Inverse Gaussian;
First order approximation;
Second order approximation;
Fractional derivatives;
Complicated systems;
Human populations;
Health state;
Health state model;
Death probability density;
Car functional state;
26A33;
35R60;
60G22;
60G40;
60H15;
60H35;
62N05;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
We develop a first exit time methodology to model the life time process of a complicated system. We assume that the functionality level of a complicated system follows a stochastic process during time and the end of the functionality of the system comes when the functionality function reaches a zero level. After solving several technical details including the Fokker-Planck equation for the appropriate boundary conditions we estimate the transition probability density function and then the first exit time probability density of the functionality of the system reaching a barrier during time. The formula we arrive is essential for complicated system forms. A simpler case has the form called as Inverse Gaussian and was first proposed independently by Schrödinger and Smoluchowsky in the same journal issue (1915) to express the probability density of a simple first exit time process hitting a linear barrier. Applications to the health state of biological systems (the human population and the Mediterranean flies) and to the functionality life time of cars are done.