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A Genetic-Based Iterative Quantile Regression Algorithm for Analyzing Fatigue Curves

Title
A Genetic-Based Iterative Quantile Regression Algorithm for Analyzing Fatigue Curves
Author
배석주
Keywords
fatigue curves; iterative quantile regression; genetic algorithms; structural risk minimization; censored data; general approximate cross-validation error
Issue Date
2012-12
Publisher
John Wiley & Sons, Ltd
Citation
Quality and Reliability Engineering International, Dec 2012, 28(8), P.897~909, 13P.
Abstract
Accurate prediction of fatigue failure times of materials such as fracture and plastic deformation at various stress ranges has a strong bearing on practical fatigue design of materials. In this study, we propose a novel genetic-based iterative quantile regression (GA-IQR) algorithm for analyzing fatigue curves that represent a nonlinear relationship between a given stress amplitude and fatigue life. We reduce the problem to a linear framework and develop the iterative algorithm for determining the model coefficients including unknown fatigue limits. The procedure keeps updating the estimates in a direction to reduce its resulting error. Also, our approach benefits from the population-based stochastic search of the genetic algorithms so that the algorithm becomes less sensitive to its initialization. Compared with conventional approaches, the proposed GA-IQR requires fewer assumptions to develop fatigue model, capable of exploring the data structure in a relatively flexible manner. All procedures and calculations are quite straightforward, such that the proposed quantile regression model has a high potential value in a wide range of applications for exploring nonlinear relationships with lifetime data. Computational results for real data sets found in the literature present good evidences to support the argument. Copyright (c) 2012 John Wiley & Sons, Ltd.
URI
http://onlinelibrary.wiley.com/doi/10.1002/qre.1280/abstracthttp://hdl.handle.net/20.500.11754/47618
ISSN
0748-8017
DOI
10.1002/qre.1280
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > INDUSTRIAL ENGINEERING(산업공학과) > Articles
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