Parameter Estimation Method of Mixture Distribution for Construction Machinery
Joint Authors
Wang, Jixin
Zhai, Xinting
Chen, Jinshi
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Due to the harsh working environment of the construction machinery, a simple distribution cannot be used to approximate the shape of the rainflow matrix.
In this paper, the Weibull-normal (W-n) mixture distribution is used.
The lowest Akaike information criterion (AIC) value is employed to determine the components number of the mixture.
A parameter estimation method based on the idea of optimization is proposed.
The method estimates parameters of the mixture by maximizing the log likelihood function (LLF) using an intelligent optimization algorithm (IOA), genetic algorithm (GA).
To verify the performance of the proposed method, one of the already existing methods is applied in the simulation study and the practical case study.
The fitting effects of the fitted distributions are compared by calculating the AIC and chi-square (χ2) value.
It can be concluded that the proposed method is feasible and effective for parameter estimation of the mixture distribution.
American Psychological Association (APA)
Zhai, Xinting& Wang, Jixin& Chen, Jinshi. 2018. Parameter Estimation Method of Mixture Distribution for Construction Machinery. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1206675
Modern Language Association (MLA)
Zhai, Xinting…[et al.]. Parameter Estimation Method of Mixture Distribution for Construction Machinery. Mathematical Problems in Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1206675
American Medical Association (AMA)
Zhai, Xinting& Wang, Jixin& Chen, Jinshi. Parameter Estimation Method of Mixture Distribution for Construction Machinery. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1206675
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206675