提出了一个非线性规划的对称对偶模型，它统一了非线性规划中两类对称模型。
In the present paper, a type of higher order dual model is formulated for minimax fractional programming problem.
由于在系统的输出方程中引入控制项，从而使相应的对偶模型的经济内涵更为深刻。
That is, a control vector is drawn into the output equation of the system.
这种模糊DEA模型可以处理不同类型的模糊数据，并且有唯一的对偶模型与之对应。
This fuzzy DEA model can accommodate various different kinds of fuzzy data and have a unique dual model to correspond with it.
接着，利用函数的上次微分构造了不可微向量优化问题（VP）的广义对偶模型，并且在适当的弱凸性条件下建立了弱对偶定理。
Finally, the generalized dual model of the problem (VP) is presented with the help of upper subdifferential of function, and a weak duality theorem is given.
该模型的动态特性可由对偶微分方程描述，它具有从状态空间内任一初始点找出多个稳定平衡点的能力。
The dynamical property of this model is described by dual differential equations and it can find out several stable equilibrium points from any initial point in the state space.
运输问题的数学模型及其特征，运输问题的求解方法（表上作业法），运输模型的进一步讨论，运输模型对偶问题分析。
The transportation models and its characters, the Transportation Simplex Method, Further discussions about the transportation models, analysis on the dual transportation problems.
运用广义网络流模型和线性规划对偶理论，提出了一种金融产品的套利定价方法。
An arbitrage pricing method for financial products in terms of generalized network model and duality theory of linear program is presented.
文中着重介绍了当对偶规划问题数学模型出现重复方程时，可通过重构原规划问题的方法，求得问题的最优解。
Emphasis is given to that when repeated equations appear in the mathematical model of the duality programming problem, global optimized solution can be obtained by reconstructing the original program.
本文给出了重力式桥墩与明挖基础整体优化设计的数学模型，选择序列线性规划法，并利用线性规划的对偶理论求最优解。
In this paper, a mathematical model for integral optimization design of pier shaft and its foundation is given, and the SLP method and duality theory are applied here to have a optimal solution.
本文从CGE模型的构建过程以及对偶线性规划、影子价格等方面阐述了线性规划理论与方法对古典经济学理论的贡献。
Initiating the construction of CGE model together with its dual linear programming and values traced, the paper expatiates the contribution o.
利用对偶规划理论对模型进行了求解。
The dual quadratic programming is applied to solving the optimal model of continuum.
通过论证用一般线性规划的对偶算法求解本模型的可行性，使得该模型的求解问题迎刃而解。
After demonstrating the feasibility of using the dual algorithm for general linear programming to solve this model, we get an effective algorithm.
运输模型进一步讨论，运输对偶问题分析，本章小节。
Further discussions about the transportation models, analysis on the dual transportation problems, summary of the Chapter 3.
针对所给出的有交易费的资产模型，引入了资产折算函数，并利用辅助鞅和凸函数对偶方法，讨论了该模型下折算资产优化的性质。
In this paper, constructs the asset conversion function for given asset model with the transaction costs and discusses some properties of asset conversion by using Martingale and dual approaches.
运用子梯度方法求解新模型的对偶问题，得到了一种新的基于对偶问题的分布式算法框架，并证明了这种新算法的收敛性。
Through analyzing the characteristic of the source algorithms and AQM at the equilibrium, we propose a new model with less constraint condition and a distribution algorithm with larger application.
采用原始-对偶内点法对该模型求解。
The authors use the primal-dual interior point method to solve the problem.
对于该模型引进了对偶几何，在此基础上得到了拟似然估计的二阶渐近性质。
A dual geometry is introduced into the model. Some second-order asymptotic results of the quasi-likelihood estimate based on the dual geometry are obtained.
提出了一个新的支持向量机模型——基于边界调节的支持向量机，并利用拉格朗日定理得到了这种支持向量机的对偶目标函数。
In order for an SVM to be more robust to noise, a new SVM model i. e., the support vector machine based on adjustive boundary SVMAB is proposed.
这两个误差模型可用来搭建基于对偶四元数的组合导航滤波器。
Both are expected to facilitate the future dual quaternion-based integrated navigation filter.
文中导出了动态导通比参数、半导体开关管拓扑以及变压器理想模型的对偶形式。
The duality of transformers (ideal and perfect models) is investigated. In addition, the duality relationships of duty ratio parameters and semiconductor-switch topologies are also given.
将优化模型转化为对偶规划，减少了设计变量的数目，并利用序列二次规划求解，缩小了模型的求解规模。
The optimization model was translated into a dual programming and solved by the sequence second-order programming. The number of the variable was reduced and the model's scale was minified.
将优化模型转化为对偶规划，减少了设计变量的数目，并利用序列二次规划求解，缩小了模型的求解规模。
The optimization model was translated into a dual programming and solved by the sequence second-order programming. The number of the variable was reduced and the model's scale was minified.
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