文章基本信息

标题：Using neural network to estimate weibull parameters
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作者：Abbasi, Babak ; Afshar nadjafi, behrouz
期刊名称：JOURNAL OF OPTIMIZATION IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING)
印刷版ISSN：2251-9904
出版年度：2010
卷号：3
期号：1
页码：48-54
语种：English
出版社：ISLAMIC AZAD UNIVERSITY, QAZVIN BRANCH
摘要：As is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. Weibull distribution involves in reliability studies frequently and has many applications in engineering. However estimating the parameters of Weibull distribution is crucial in classical ways. This distribution has three parameters, but for simplicity, a parameter is ridded off and as a result, the estimation of the others will be easily done. When the three-parameter distribution is of interest, the classical estimation procedures such as maximum likelihood estimation (MLE) will be quite boring. In this paper to take advantage of application of artificial neural networks (ANN) to statistics, we propose using a simple neural network to estimate three parameters of Weibull distribution simultaneously. Trained neural network similar to moment method estimates Weibull parameters based on mean, standard deviation, median, skewness and kurtosis of the sample accurately. To assess the power of the proposed method we carry out simulation study and compare the results of the proposed method with real values of the parameters.
关键词：Artificial neural networks; parameters estimate; tree- parameter weibull