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最大熵分位值估计及其对偶型优化解法
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Affiliation of Author(s):能源与动力学院

Journal:航空动力学报

Key Words:分位值估计;对偶型;最大熵;逐次优化;概率权重矩;

Abstract:针对经典最大熵分位值估计中拉格朗日系数计算目前存在高度非线性、计算结果精度不高或有时难以收敛等问题,提出了一种对偶型-逐次寻优的方法.基于拉格朗日对偶法,推导建立了含有拉格朗日系数优化函数的对偶表达式;在此基础上,基于样本的概率权重矩约束,提出了逐次寻优算法.针对几种常见的概率分布类型和一种较为复杂的概率分布类型,采用对偶型最大熵方法和经典最大熵方法对其概率累积函数和分位值进行计算对比分析表明:对偶型最大熵分位值估计不仅具有非线性程度低、形式简单,而且对偶型-逐次寻优的方法具有比较高的计算精度,优化迭代的收敛性好等特点.

Translation or Not:no

Date of Publication:2017-03-01

Co-author:吴福仙

Correspondence Author:wwd

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Professor

Gender:Male

Alma Mater:南京航空航天大学

Education Level:With Certificate of Graduation for Doctorate Study

Degree:Doctoral Degree in Engineering

School/Department:College of Energy and Power Engineering

Discipline:Aerospace Propulsion Theory and Engineering. Power Machinery and Engineering

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