Results 281 to 290 of about 28,090,256 (352)
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Matroids and a Reliability Analysis Problem
Mathematics of Operations Research, 1979We present an algorithm for the reliability analysis problem of determining the probability that a stochastic binary system operates. The stochastic binary system is viewed as an independence system. The algorithm finds a partition of the set of independence sets into subsets called intervals.
Michael O. Ball, George L. Nemhauser
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Copula-based reliability analysis of degrading systems with dependent failures
Reliability Engineering & System Safety, 2020Consider a coherent system, in which the degradation processes of its performance characteristics are positively correlated, this paper systematically investigates a bivariate degradation model of such a system.
Guanqi Fang, R. Pan, Yili Hong
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A novel learning function based on Kriging for reliability analysis
Reliability Engineering & System Safety, 2020Adaptively constructing the surrogate model for reliability analysis has been widely studied for the advantage of guaranteeing the estimation accuracy while calling the real performance function as little as possible.
Yan Shi +4 more
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A Moment Approach to Positioning Accuracy Reliability Analysis for Industrial Robots
IEEE Transactions on Reliability, 2020The uncertain variables of the link dimensions and joint clearances, whose deviation is caused by manufacturing and assembling errors, have a considerable influence on the positioning accuracy of industrial robots.
Jinhui Wu +3 more
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Kinematic Reliability Analysis of Robotic Manipulator
Journal of Mechanical Design, 2020Kinematic reliability of robotic manipulators is the linchpin for restraining the positional errors within acceptable limits. This work develops an efficient reliability analysis method to account for random dimensions and joint angles of robotic ...
Dequan Zhang, Xu-hao Han
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System reliability analysis by combining structure function and active learning kriging model
Reliability Engineering & System Safety, 2020Surrogate models are useful for reducing the computational burden in real applications. Structural reliability analyses based on active learning kriging models, such as efficient global reliability analysis (EGRA) and an active learning method to combine
Kai Yuan +3 more
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2020
As the integration of components are increasing from VLSI to ULSI level. This may lead to damage of electronic system because each component has its own operating characteristics and conditions. So, health prognostic techniques are used that comprise a deep insight into failure cause and effects of all the components individually as well as an ...
Jérôme Morio +2 more
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As the integration of components are increasing from VLSI to ULSI level. This may lead to damage of electronic system because each component has its own operating characteristics and conditions. So, health prognostic techniques are used that comprise a deep insight into failure cause and effects of all the components individually as well as an ...
Jérôme Morio +2 more
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IBM Systems Journal, 1983
Methods proposed for software reliability prediction are reviewed. A case study is then presented of the analysis of failure data from a Space Shuttle software project to predict the number of failures likely during a mission, and the subsequent verification of these predictions.
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Methods proposed for software reliability prediction are reviewed. A case study is then presented of the analysis of failure data from a Space Shuttle software project to predict the number of failures likely during a mission, and the subsequent verification of these predictions.
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Reliability Engineering & System Safety, 2019
Structural reliability analysis is typically evaluated based on a multivariate function that describes underlying failure mechanisms of a structural system.
Xufang Zhang, Lei Wang, J. Sørensen
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Structural reliability analysis is typically evaluated based on a multivariate function that describes underlying failure mechanisms of a structural system.
Xufang Zhang, Lei Wang, J. Sørensen
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Deep learning for high-dimensional reliability analysis
, 2020High-dimensional reliability analysis remains a grand challenge since most of the existing methods suffer from the curse of dimensionality. This paper introduces a novel high-dimensional data abstraction (HDDA) framework for dimension reduction in ...
Mingyang Li, Zequn Wang
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