Modeling energy spreads with a generalized novel mean-reverting stochastic process

Author(s):  
Mir Hashem Moosavi Avonleghi ◽  
Matt Davison
Keyword(s):  
2007 ◽  
Vol 44 (02) ◽  
pp. 393-408 ◽  
Author(s):  
Allan Sly

Multifractional Brownian motion is a Gaussian process which has changing scaling properties generated by varying the local Hölder exponent. We show that multifractional Brownian motion is very sensitive to changes in the selected Hölder exponent and has extreme changes in magnitude. We suggest an alternative stochastic process, called integrated fractional white noise, which retains the important local properties but avoids the undesirable oscillations in magnitude. We also show how the Hölder exponent can be estimated locally from discrete data in this model.


2013 ◽  
Author(s):  
Friedel Bolle ◽  
Philipp E. Otto
Keyword(s):  

1984 ◽  
Vol 16 (8-9) ◽  
pp. 131-138 ◽  
Author(s):  
Johannes Brummer

Problems in the construction of design storms are expressed in mathematical terms. Introduced here is a concept for approximating natural peak flow values by means of the distribution of typical rainfall patterns. A comparison demonstrates the quality of this concept and the competency of some well-known design storms for the adequate evaluation of peak flows.


2020 ◽  
Vol 14 ◽  
Author(s):  
Dangbo Du ◽  
Jianxun Zhang ◽  
Xiaosheng Si ◽  
Changhua Hu

Background: Remaining useful life (RUL) estimation is the central mission to the complex systems’ prognostics and health management. During last decades, numbers of developments and applications of the RUL estimation have proliferated. Objective: As one of the most popular approaches, stochastic process-based approach has been widely used for characterizing the degradation trajectories and estimating RULs. This paper aimed at reviewing the latest methods and patents on this topic. Methods: The review is concentrated on four common stochastic processes for degradation modelling and RUL estimation, i.e., Gamma process, Wiener process, inverse Gaussian process and Markov chain. Results: After a briefly review of these four models, we pointed out the pros and cons of them, as well as the improvement direction of each method. Conclusion: For better implementation, the applications of these four approaches on maintenance and decision-making are systematically introduced. Finally, the possible future trends are concluded tentatively.


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