Taiwan depository receipts forecasting along a novel regular Markov chain model

Huang, Wen‐Tzeng; Chen, Gary Yu-Hsin; Chen, Ping-Shun

doi:10.1080/02533839.2020.1751721

Cited by 4 publications

(1 citation statement)

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“…Markov process is a stochastic process without forward looking and after delay. Ay took advantage of Markov processes carrying out the reliability analysis of system failure [32], Rajesh improved the future trends in the resilience of the town center based on the grey moving probability state Markov model [33], Patelli addressed the problem of community detection in networks by introducing a general definition of Markov stability [34], Huang introduces a new Markov chain model to forecast price trends [35]. Therefore, under the premise of obeying the Markov process, PageRank is applied, the transfer relation of the system fault in each subsystem is regarded as the interlink relation of the page in the Internet, and each subsystem is abstracted into the Internet page, and user browsing the page in the direction of the page link is regarded as the delivery of the failure between subsystems [36], so as to quantify the influence relationship between the correlation subsystems, realize the quantitative analysis of the influence degree, and improve rationality and accuracy of the influence relation analysis.…”

Section: Applicationmentioning

confidence: 99%

Importance Analysis of System Related Fault Based on Improved Decision-Making Trial and Evaluation Laboratory

Guixiang

2022

Measurement Science Review

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The existence of related faults between components brings great difficulties to the analysis of the importance of system components. How to quantify the influence of related faults and evaluate the importance of components is one of the hot issues in current research. In this paper, under the assumption that the fault propagation obeys the Markov process, the PageRank algorithm is integrated into the decision-making trial and evaluation laboratory (DEMATEL). On the basis, the calculation of influencing degree and influenced degree between components is studied to quantify the influence of related faults, and the problem of subjective evaluation of weight coefficient in traditional DEMATEL is solved. The rationality is verified through the method of combining the Interpretative Structural Modeling Method (ISM) and direct relation matrix. The importance of system related faults is identified accurately based on the calculation of center degree and cause degree, and the central-related faults of CNC machine tools are analyzed as an example to verify the effectiveness of the proposed method.

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