Related references
Note: Only part of the references are listed.Statistical models for estimating the fatigue life, the stress-life relation, and the P-S-N curves of metallic materials in Very High Cycle Fatigue: A review
Andrea Tridello et al.
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES (2022)
Statistical analysis of wind energy potential using different estimation methods for Weibull parameters: a case study
Mohammed Wadi et al.
ELECTRICAL ENGINEERING (2021)
Selection of Efficient Parameter Estimation Method for Two-Parameter Weibull Distribution
Mohammed M. A. Almazah et al.
MATHEMATICAL PROBLEMS IN ENGINEERING (2021)
Estimation of reliability for multi-component stress-strength model based on modified Weibull distribution
M. S. Kotb et al.
STATISTICAL PAPERS (2021)
A review on genetic algorithm: past, present, and future
Sourabh Katoch et al.
MULTIMEDIA TOOLS AND APPLICATIONS (2021)
Fuzzy approach in modeling static and fatigue strength of composite materials and structures
Aleksander Muc
NEUROCOMPUTING (2020)
Manufacturing effects on fatigue strength
Moises Jimenez-Martinez
ENGINEERING FAILURE ANALYSIS (2020)
Fatigue-Life Prediction of Mechanical Element by Using the Weibull Distribution
Jesus M. Barraza-Contreras et al.
APPLIED SCIENCES-BASEL (2020)
Correction Factor for Unbiased Estimation of Weibull Modulus by the Linear Least Squares Method
Xiang Jia et al.
METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE (2019)
A nonlinear grey forecasting model with double shape parameters and its application
Xiaomei Liu et al.
APPLIED MATHEMATICS AND COMPUTATION (2019)
Life prediction for a vacuum fluorescent display based on two improved models using the three-parameter Weibull right approximation method
Jianping Zhang et al.
LUMINESCENCE (2018)
Unbiased estimation of Weibull modulus using linear least squares analysis-A systematic approach
Ian J. Davies
JOURNAL OF THE EUROPEAN CERAMIC SOCIETY (2017)
Weibull Modulus Estimated by the Non-linear Least Squares Method: A Solution to Deviation Occurring in Traditional Weibull Estimation
T. Li et al.
METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE (2017)
An improved modeling for life prediction of high-power white LED based on Weibull right approximation method
Jianping Zhang et al.
MICROELECTRONICS RELIABILITY (2016)
Reliability of a Weibull analysis using the maximum-likelihood method
Milan Ambrozic et al.
JOURNAL OF MATERIALS SCIENCE (2011)
A Comparison of Maximum Likelihood and Median-Rank Regression for Weibull Estimation
Ulrike Genschel et al.
QUALITY ENGINEERING (2010)
The Evaluation of Median-Rank Regression and Maximum Likelihood Estimation Techniques for a Two-Parameter Weibull Distribution
Denisa Olteanu et al.
QUALITY ENGINEERING (2010)
Statistical estimation for the parameters of Weibull distribution based on progressively type-I interval censored sample
Hon Keung Tony Ng et al.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION (2009)
On initial populations of a genetic algorithm for continuous optimization problems
Heikki Maaranen et al.
JOURNAL OF GLOBAL OPTIMIZATION (2007)
Genetic algorithm to maximize a lower-bound for system time-to-failure with uncertain component Weibull parameters
DW Coit et al.
COMPUTERS & INDUSTRIAL ENGINEERING (2002)