Reliability modeling for intermittent working system based on Wiener process

2021 ◽  
pp. 107599
Author(s):  
Haizhen Zhu ◽  
Xueqi Wang ◽  
Mingqing Xiao ◽  
Zhao Yang ◽  
Xilang Tang ◽  
...  
Keyword(s):  
Wiener Process ◽  
Reliability Modeling

Method for the reliability modeling of selfrepairing onboard information systems

1998 ◽  
Vol 4 (4) ◽  
pp. 55-60
Author(s):  
B.A. Mandziy ◽  
◽  
V.P. Belyaev ◽  
B.Yu. Volotchiy ◽  
◽  
...  
Keyword(s):  
Information Systems ◽  
Reliability Modeling

A Note on Shot-Noise and Reliability Modeling,

1984 ◽  
Author(s):  
A. J. Lemoine ◽  
M. L. Wenocur
Keyword(s):  
Shot Noise ◽  
Reliability Modeling

Forecasting based on spectral time series analysis: prediction of the Aurubis stock price

2020 ◽  
Vol 17 (4) ◽  
pp. 215-227
Author(s):  
Julia Babirath ◽  
Karel Malec ◽  
Rainer Schmitl ◽  
Kamil Maitah ◽  
Mansoor Maitah
Keyword(s):  
Time Series ◽  
Risk Management ◽  
Time Series Analysis ◽  
Wiener Process ◽  
Stock Price ◽  
Percentage Error ◽  
Portfolio Performance ◽  
Stock Price Prediction ◽  
Series Analysis ◽  
Augmented Dickey Fuller

The attempt to predict stock price movements has occupied investors ever since. Reliable forecasts are a basis for investment management, and improved forecasting results lead to enhanced portfolio performance and sound risk management. While forecasting using the Wiener process has received great attention in the literature, spectral time series analysis has been disregarded in this respect. The paper’s main objective is to evaluate whether spectral time series analysis can produce reliable forecasts of the Aurubis stock price. Aurubis poses a suitable candidate for an investor’s portfolio due to its sound economic and financial situation and the steady dividend policy. Additionally, reliable management contributes to making Aurubis an investment opportunity. To judge if the achieved forecast results can be considered satisfactory, they are compared against the simulation results of a Wiener process. After de-trending the time series using an Augmented Dickey-Fuller test, the residuals were compartmentalized into sine and cosine functions. The frequencies, amplitude, and phase were obtained using the Fast Fourier transform. The mean absolute percentage error measured the accuracy of the stock price prediction, and the results showed that the spectral analysis was able to deliver superior results when comparing the simulation using a Wiener process. Hence, spectral time series can enhance stock price forecasts and consequently improve risk management.

Reliability modeling for multistage systems subject to competing failure processes

2021 ◽  
Author(s):  
Hao Lyu ◽  
Zaiyou Yang ◽  
Shuai Wang ◽  
Yaping Zhao ◽  
Michael Pecht
Keyword(s):  
Reliability Modeling
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