Personnel BDAR Ability Assessment Model Based on Bayesian Stochastic Assessment Method

Zhi-feng You (), Tian-bin Liu, Ning Ding and Kai-xuan Cui
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Zhi-feng You: Mechanical Engineering College
Tian-bin Liu: Mechanical Engineering College
Ning Ding: Mechanical Engineering College
Kai-xuan Cui: Mechanical Engineering College

Chapter Chapter 43 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 419-426 from Springer

Abstract: Abstract It is important for us to evaluate each trainee’s ability with the aim of improving BDAR training efficiency. The typical assessment methods include fuzzy evaluation, gray correlation evaluation, neural network and so on. All of these methods are not able to make full use of the historical information. Determining membership function in first two methods is not easy. And ANN needs a lot of data sample which is difficult to obtain in BDAR training. So we can’t use these methods to model the assessment of personnel BDAR ability. Then we introduce Bayesian Stochastic Assessment Method which can deal well with the nonlinear and random problem. Each indexes’ standard is given according to the characteristics of BDAR training. A modified normal distribution which can make full use of historical information was put forward to determine the prior probability. And the poster probability is determined by distance method.

Keywords: Bayesian; Stochastic assessment; Bayesian theorem; Personnel BDAR ability; Prior probability (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38391-5_43

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DOI: 10.1007/978-3-642-38391-5_43

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