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lagrangian multiplier中文是什么意思

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用"lagrangian multiplier"造句"lagrangian multiplier"怎么读"lagrangian multiplier" in a sentence

中文翻译手机手机版

  • 拉格朗乘数
  • 拉氏乘数

例句与用法

  • In normed space , the theorem of existence of lagrangian multipliers is proved , and - super saddle point is defined , and the relations between - super saddle point and existence of - super efficient solution are discuss . based on these , lagrange - super dual results of set - valued optimization problem are given , including weak duality , strong duality , converse duality etc
    在赋范空间中,证明了lagrangian乘子存在性定理,定义了-超鞍点的概念,探讨了-超鞍点与-超有效解存在性之间的关系。
  • The stationary conditions of the least complementary principle had different forms . in this paper , by using the adding zero transformation and the lagrangian multiplier method , the stationary condition of the least complementary principle is derived and it satisfies the completeness of varied conditions for variational principles in elastic mechanics
    最小余能原理的驻值条件也曾有过不同的提法,本文应用加零变换和拉氏乘子法推导了最小余能原理的驻值条件,它应满足弹性力学变分原理各类条件的完备性。
  • This paper summarized the characteristic and localizations of the special contact elements that can simulate the joints in rockmass . except for those , three kinds of numerical methods for dynamic contact analysis were introduced . then , the augment lagrangian method that combined lagrangian multiplier and penalty function was applied to the dynamic contact analysis with friction
    本文阐述了模拟岩体裂隙节理的特殊接触面单元,分析其特点和局限性;介绍了三种处理动力接触问题的数值算法,利用lagrange乘子法和罚函数法联合的增广lagrange乘子法建立起裂隙节理的动力摩擦接触条件和本构方程以及有限元基本方程,并运用此数值方法分析一具有贯通节理面的动力摩擦接触问题,得出一些基本规律。
  • According to the different sample set , we have been on discussion , using lagrangian multiplier technique or lmt in the optimal theory , slt and function analysis , then we get the decision function and svm with the corresponding different sample set . thirdly , for improving generalization ability , application ability and recognition speed of svm , we have used fuzzy set theory ( fst ) and rough set theory to study svm deep , and integrated them into svm , constructed fssvm ( fuzzy set svm ) and svm based on rough set theory , and extended performances of svm in the chapter 4 , 5
    再次,为了进一步提高支持向量机的通用性以及推广能力、应用能力、识别速度等性能,在第四、第五两章运用模糊集理论( fst )和粗糙集理论( rst )对支持向量机进行研究,采用优势互补原则,先是把模糊集与支持向量机有机结合,构造出基于模糊集的支持向量机( fssvm ) ,然后把粗糙集理论与支持向量机相互结合,进而把rst与fssvm相互结合,构造出基于rst的支持向量机。
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