Expectation Bayesian Estimation of System Reliability Based on Failures

Gholizadeh, Ramin; Londoño, Sergio Luis Mercado; Barahona, Manuel J. P.

doi:10.1007/s11009-018-9656-x

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…where P (Reduction) is the risk reduction probability, P (response) is the probability that a given vehicle does not reach the affected road segment after receiving the warning signal, N v is the average number of vehicles, and R (h) is the hybrid model reliability. The overall reliability of the two detection and prediction models connected in parallel is calculated according to Equation (6) [51]:…”

Section: Hybrid Risk Reduction Modelmentioning

confidence: 99%

Hybrid Early Warning System for Rock-Fall Risks Reduction

et al. 2021

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Rock-fall is a natural threat resulting in many annual economic costs and human casualties. Constructive measures including detection or prediction of rock-fall and warning road users at the appropriate time are required to prevent or reduce the risk. This article presents a hybrid early warning system (HEWS) to reduce the rock-fall risks. In this system, the computer vision model is used to detect and track falling rocks, and the logistic regression model is used to predict the rock-fall occurrence. In addition, the hybrid risk reduction model is used to classify the hazard levels and delivers early warning action. In order to determine the system’s performance, this study adopted parameters, namely overall prediction performance measures, based on a confusion matrix and reliability. The results show that the overall system accuracy was 97.9%, and the reliability was 0.98. In addition, a system can reduce the risk probability from (6.39 × 10−3) to (1.13 × 10−8). The result indicates that this system is accurate, reliable, and robust; this confirms the purpose of the HEWS to reduce rock-fall risk.

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Section: Hybrid Risk Reduction Modelmentioning

confidence: 99%

Hybrid Early Warning System for Rock-Fall Risks Reduction

et al. 2021

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“…Simulation test on several examples with different complexity shows that heuristic algorithm was more accurate than classical algorithm [6]. Gholizadeh and other scholars analyzed the Bayesian estimation for the electronic system and pointed out that if the faults were independent, E-Bayesian algorithm can improve the accuracy of analysis [7]. Zhang et al [8] analyzed the multi-scale security system for micro-mini smart ammunition.…”

Section: Introductionmentioning

confidence: 99%

Improved shuffled frog leaping algorithm on system reliability analysis

Yan

2019

Brain Inf.

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With the increase in system complexity, the intelligent heuristic optimization methods have received more and more attention on system reliability analysis. However, the objective functions and constraint conditions of system reliability are nonlinear. Thereby, a hybrid optimization method was proposed, based on the shuffled frog leaping algorithm and bacterial foraging algorithm, to solve the problem of system reliability and redundancy allocation. First, random grouping strategy was added to maintain the diversity of the population. Then, the Levy flight update strategy was used to increase the global search ability. Finally, the method of migration operation was introduced to escape from local optimums. The proposed methodology, a new version of the SFLA algorithm, was then applied to the mathematical test and the operation of the system reliability model, respectively. Results show that compared to the common methods, it can obtain the best solution, with the maximum value of the system reliability.

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Study on the effect of the different prior distributions on E-Bayesian estimation of failure probability and its E-posterior risk

Ming

2020

Communications in Statistics - Simulation and Computation

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Expectation Bayesian Estimation of System Reliability Based on Failures

Cited by 4 publications

References 7 publications

Hybrid Early Warning System for Rock-Fall Risks Reduction

Hybrid Early Warning System for Rock-Fall Risks Reduction

Improved shuffled frog leaping algorithm on system reliability analysis

Study on the effect of the different prior distributions on E-Bayesian estimation of failure probability and its E-posterior risk

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