Success Probability Assessment Based on Information Entropy
The Bayesian method is superior to the classical statistical method on condition of small sample test. However, its evaluation results are not so good if subjective prior information is intervened. The success probability assessment about the success or failure tests of weapon products focussed in this paper, and a fusing evaluation method based on information entropy is proposed. Firstly, data from equivalent surrogate tests is converted into the prior information of an equivalent source by the information entropy theory. Secondly, the prior distribution of the success probability is identified via the Bootstrap method, and the posterior distribution is provided by the Bayesian method with the information of prototype tests in succession. Lastly, an example is given, and the results show that the proposed method is effective and valuable.
Defence Science Journal, 2010, 60(3), pp.271-275, DOI:http://dx.doi.org/10.14429/dsj.60.353
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