An univariate DEMR modelling on repair effects

• Autorzy: Guo R.
• Języki publikacji: EN

Abstrakty

EN

Repairable system analysis is in nature an evaluation of repair effects. Recent tendency in reliability engineering literature was estimating system repair effects or linking repair to certain covariate to extract repair impacts by imposing repair regimes during system reliability analysis. In this paper, we develop a differential equation motivated regression (abbreviated as DEMR) model with a random fuzzy error term based on the axiomatic framework of self-dual fuzzy credibility measure theory proposed by Liu [5] and grey differential equation models. The fuzzy variable indexes the random fuzzy error term will be used to facilitate the evaluation of repair effects. We further propose a parameter estimation approach for the fuzzy variable (repair effect) under the maximum entropy principle.

Słowa kluczowe

EN

grey theory; DEMR; differential equation motivated regression; repair effect; credibility measure theory; random fuzzy variable

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2007
• Tom: Vol. 1
• Strony: 157--165
• Opis fizyczny: Bibliogr. 6 poz., tab., wykr.

Twórcy

autor

Guo R.

• University of Cape Town, Cape Town, South Africa

Bibliografia

• [1] De Luca, A. & Termini, S. (1972). A Definition of Non-probabilistic Entropy in the Setting of Fuzzy Sets Theory. Information and Control 20, 301-312.
• [2] Deng, J. L. (1985). Grey Systems (Social Economical). The Publishing House of Defence Industry, Beijing (in Chinese).
• [3] Guo, R. (2005a). Repairable System Modelling Via Grey Differential Equations. Journal of Grey System, 8 (1), 69-91.
• [4] Guo, R. (2005b). A Repairable System Modelling by Combining Grey System Theory with Interval-Valued Fuzzy Set Theory. International Journal of Reliability, Quality and Safety Engineering, 12 (3), 241-266.
• [5] Liu, B. (2004). Uncertainty Theory: An Introduction to Its Axiomatic Foundations. Springer-Verlag Heidelberg, Berlin.
• [6] Li, P. & Liu, B. Entropy of Credibility Distributions for Fuzzy Variables. IEEEE Transactions on Fuzzy Systems, ( to be published).