Reliability Analysis Based on Nonhomogeneous Continuous-Time Markov Modeling with Application to Repairable Pumps of a Power Plant

To avoid equipment breakdown that may result in power outage, equipment maintenance is very important. However, maintenance is always accompanied with cost and operating performance. Finding a balance between reducing risk of power outage and increasing cost through maintenance becomes an important issue for power plant owners. To this end, a repair-related analytical model by nonhomogeneous continuous-time Markov chain is constructed in this study. To consider the maintenance process which accords with the actual situations, we add not only the effect of time but also environmental factors for failure rate and repair rate into consideration to describe uncertainties of the process. Since it is difficult to obtain the analytic solution of transition rate in a nonhomogeneous continuous-time Markov chain, we propose a method to find the numerical solution. In the end, the failure and repair data of pumps of a local power plant are applied into the proposed model. An optimal solution in consideration of the life cycle cost under a certain availability constraint is found through the model.

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Double-Layer Network Negative Public Opinion Information Propagation Modeling Based on Continuous-Time Markov Chain

The Computer Journal ◽

10.1093/comjnl/bxaa038 ◽

2020 ◽

Author(s):

Xiaoyang Liu ◽

Ting Tang ◽

Daobing He

Keyword(s):

Markov Chain ◽

Public Opinion ◽

Double Layer ◽

Continuous Time ◽

Effective Control ◽

Information Propagation ◽

Continuous Time Markov Chain ◽

Negative Opinion ◽

Proposed Model ◽

Propagation Network

Abstract In view of the fact that the existing public opinion propagation aspects are mostly based on single-layer propagation network, these works rarely consider the double-layer network structure and the negative opinion evolution. This paper proposes a new susceptible-infected-vaccinated-susceptible negative opinion information propagation model with preventive vaccination by constructing double-layer network topology. Firstly, the continuous-time Markov chain is used to simulate the negative public opinion information propagation process and the nonlinear dynamic equation of the model is derived; secondly, the steady state condition of the virus propagation in the model is proposed and mathematically proved; finally, Monte Carlo method is applied in the proposed model. The parameters of simulation model have an effect on negative public opinion information propagation, the derivation results are verified by computer simulation. The simulation results show that the proposed model has a larger threshold of public opinion information propagation and has more effective control of the scale of negative public opinion; it also can reduce the density of negative public opinion information propagation and suppress negative public opinion information compared with the traditional susceptible infected susceptible model. It also can provide the scientific method and research approach based on probability statistics for the study of negative public opinion information propagation in complex networks.

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A STOCHASTIC MODEL FOR GERMINATION

Revista de Matemática Teoría y Aplicaciones ◽

10.15517/rmta.v27i2.34109 ◽

2020 ◽

Vol 27 (2) ◽

pp. 375-385

Author(s):

JOSÉ VILLA-MORALES

Keyword(s):

Experimental Data ◽

Markov Chain ◽

Stochastic Model ◽

Continuous Time ◽

Continuous Time Markov Chain ◽

Germination Time ◽

Germination Process ◽

Proposed Model

Assuming that the germination process of a seed passes through several stages (or states), including a state of non-germination, we model this phenomenon by means of a continuous-time Markov chain. The distribution of the germination time and the average of the first germination is obtained. In particular, when the duration of the process at each stage is on average the same we see that the proposed model adjusts rather well some experimental data.

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Optimal Consumption and Insurance: A Continuous-time Markov Chain Approach

Astin Bulletin ◽

10.2143/ast.38.1.2030412 ◽

2008 ◽

Vol 38 (01) ◽

pp. 231-257 ◽

Cited By ~ 17

Author(s):

Holger Kraft ◽

Mogens Steffensen

Keyword(s):

Continuous Time ◽

Optimal Solution ◽

Decision Problems ◽

Optimal Consumption ◽

Continuous Time Markov Chain ◽

Financial Decision Making ◽

Markov Chain Approach ◽

Special Cases ◽

Financial Decision ◽

The Individual

Personal financial decision making plays an important role in modern finance. Decision problems about consumption and insurance are in this article modelled in a continuous-time multi-state Markovian framework. The optimal solution is derived and studied. The model, the problem, and its solution are exemplified by two special cases: In one model the individual takes optimal positions against the risk of dying; in another model the individual takes optimal positions against the risk of losing income as a consequence of disability or unemployment.

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