Parameter Estimation of Mixed Weibull Distributions Using Cuckoo Search

被引:0
|
作者
池阔 [1 ]
王广彦 [1 ]
康建设 [1 ]
吴坤 [1 ]
机构
[1] Department of Equipment Command and Management,Mechanical Engineering College
关键词
reliability; mixed Weibull distribution; parameter estimation; Cuckoo search(CS);
D O I
10.19884/j.1672-5220.2016.02.015
中图分类号
TB114.3 [可靠性理论]; TK423 [构造];
学科分类号
摘要
The lifetime data of products with multiple failure modes which are collected from life testing are often fitted by the mixed Weibull distributions. Since the mixed Weibull distributions contain no less than five parameters,the parameter estimation is difficult and inaccurate. In order to enhance the accuracy,a new method of parameter estimation based on Cuckoo search( CS) is proposed. An optimization model for the mixed Weibull distribution is formulated by minimizing the residual sum of squares. The optimal parameters are searched via CS algorithm. In the case study,the lifetime data come from the life testing of diesel injectors and are fitted by the twocomponent Weibull mixture. Regarding the maximum absolute error and the accumulative absolute error between estimated and observed values as the accuracy index of parameter estimation,the results of four parameter estimation methods that the graphic estimation method,the nonlinear least square method,the optimization method based on particle swarm optimization( PSO) and the proposed method are compared. The result shows that the proposed method is more efficient and more accurate than the other three methods.
引用
收藏
页码:235 / 238
页数:4
相关论文
共 50 条
  • [41] Revisiting Maximum Log-Likelihood Parameter Estimation for Two-Parameter Weibull Distributions: Theory and Applications
    Kneib, Thomas
    Schlueter, Jan-Christian
    Wacker, Benjamin
    RESULTS IN MATHEMATICS, 2024, 79 (06)
  • [42] GRAPHICAL ESTIMATION METHODS FOR WEIBULL DISTRIBUTIONS
    CRAN, GW
    MICROELECTRONICS AND RELIABILITY, 1976, 15 (01): : 47 - 52
  • [43] Search Dynamics Analysis and Adaptive Parameter Adjustment of Cuckoo Search
    Kumagai, Wataru
    Tamura, Kenichi
    Yasuda, Keiichiro
    2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS, 2015, : 1700 - 1705
  • [44] Weibull distributions when the shape parameter is defined
    Bowman, KO
    Shenton, LR
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2001, 36 (03) : 299 - 310
  • [45] Weibull and Gamma distributions for Wave Parameter Predictions
    Satheesh, S. P.
    Praveen, V. K.
    Kumar, V. Jagadish
    Muraleedharan, G.
    Kurup, P. G.
    JOURNAL OF INDIAN GEOPHYSICAL UNION, 2005, 9 (01): : 55 - 64
  • [46] Adding a parameter to the exponential and Weibull distributions with applications
    Gomez-Deniz, E.
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2018, 144 : 108 - 119
  • [47] On best estimation for parameter weibull distribution
    Alkutubi, Hadeel Salim
    World Academy of Science, Engineering and Technology, 2011, 51 : 281 - 283
  • [48] Inference of sampling on Weibull parameter estimation
    Jacquelin, J
    IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 1996, 3 (06) : 809 - 816
  • [49] Parameter estimation of the Weibull probability distribution
    Pang, WK
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2004, 735 : 549 - 554
  • [50] PARAMETER-ESTIMATION FOR WEIBULL DISTRIBUTION
    STONE, GC
    VANHEESWIJK, RG
    IEEE TRANSACTIONS ON ELECTRICAL INSULATION, 1977, 12 (04): : 253 - 261