Jaya algorithm in estimation of P[X>Y] for two parameter Weibull distribution

被引:3
作者
Raikar, Saurabh L. [1 ]
Gaonkar, Rajesh S. Prabhu [2 ]
机构
[1] Goa Univ, Mech Engn Dept, Goa Coll Engn, Ponda 403401, Goa, India
[2] Indian Inst Technol Goa IIT Goa, Ponda 403401, Goa, India
来源
AIMS MATHEMATICS | 2022年 / 7卷 / 02期
关键词
reliability; Weibull distribution; parameter estimation; optimization; Jaya algorithm; PARTICLE SWARM OPTIMIZATION; MODEL;
D O I
10.3934/math.2022156
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Jaya algorithm is a highly effective recent metaheuristic technique. This article presents a simple, precise, and faster method to estimate stress strength reliability for a two-parameter, Weibull distribution with common scale parameters but different shape parameters. The three most widely used estimation methods, namely the maximum likelihood estimation, least squares, and weighted least squares have been used, and their comparative analysis in estimating reliability has been presented. The simulation studies are carried out with different parameters and sample sizes to validate the proposed methodology. The technique is also applied to real-life data to demonstrate its implementation. The results show that the proposed methodology's reliability estimates are close to the actual values and proceeds closer as the sample size increases for all estimation methods. Jaya algorithm with maximum likelihood estimation outperforms the other methods regarding the bias and mean squared error.
引用
收藏
页码:2820 / 2839
页数:20
相关论文
共 45 条
[1]   Estimating the parameters of Weibull distribution using simulated annealing algorithm [J].
Abbasi, Babak ;
Jahromi, Abdol Hamid Eshragh ;
Arkat, Jamal ;
Hosseinkouchack, Mehdi .
APPLIED MATHEMATICS AND COMPUTATION, 2006, 183 (01) :85-93
[2]   Parametric inference of Akash distribution for Type-II censoring with analyzing of relief times of patients [J].
Abushal, Tahani A. .
AIMS MATHEMATICS, 2021, 6 (10) :10789-10801
[3]   A new approach for estimating the parameters of Weibull distribution via particle swarm optimization: An application to the strengths of glass fibre Cheek tor data [J].
Acitas, Sukru ;
Aladag, Cagdas Hakan ;
Senoglu, Birdal .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 183 :116-127
[4]  
Aggarwala R., 2002, ADV METHODOLOGICAL A
[5]   On estimation procedures of stress-strength reliability for Weibull distribution with application [J].
Almarashi, Abdullah M. ;
Algarni, Ali ;
Nassar, Mazen .
PLOS ONE, 2020, 15 (08)
[6]   Bayesian non-parametric frailty model for dependent competing risks in a repairable systems framework [J].
Almeida, Marco Pollo ;
Paixao, Rafael S. ;
Ramos, Pedro L. ;
Tomazella, Vera ;
Louzada, Francisco ;
Ehlers, Ricardo S. .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 204
[7]   Bayesian and non-Bayesian reliability estimation of multicomponent stress-strength model for unit Weibull distribution [J].
Alotaibi, Refah Mohammed ;
Tripathi, Yogesh Mani ;
Dey, Sanku ;
Rezk, Hoda Ragab .
JOURNAL OF TAIBAH UNIVERSITY FOR SCIENCE, 2020, 14 (01) :1164-1181
[8]   Exponentiated power Lindley distribution [J].
Ashour, Samir K. ;
Eltehiwy, Mahmoud A. .
JOURNAL OF ADVANCED RESEARCH, 2015, 6 (06) :895-905
[9]   Stress-Strength Reliability for Exponentiated Inverted Weibull Distribution with Application on Breaking of Jute Fiber and Carbon Fibers [J].
Azm, Wael S. Abu El ;
Almetwally, Ehab M. ;
Alghamdi, Abdulaziz S. ;
Aljohani, Hassan M. ;
Muse, Abdisalam Hassan ;
Abo-Kasem, O. E. .
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021, 2021
[10]  
Bader M., 1982, PROGR SCI ENG COMPOS, P1129, DOI DOI 10.12691/AJAMS-6-5-5