根据显示原理，采用最优控制理论求解模型。
Following the revelation principle, we solves the model by employing the optimal control theory.
为了求解模型提出构建综合运输网络模型的方法。
Moreover, in order to solve the model, a method to construct the integrated transport network is put forward.
提出了一种基于零件设计过程的约束维护及求解模型。
A model for constraints maintenance and solution is proposed in this paper based on the design process of parts.
针对模型的特点设计了求解模型的特殊PSO算法。
Specific particle swarm optimization (PSO) algorithm is designed to solve the model.
文中对匈牙利算法的起源、运用、求解模型及其原理作了介绍。
The origin of Hungarian algorithm, its application, the solution model as well as its principle will be introduced in this article.
证明了模型解的等价性和唯一性，给出了求解模型的MSA算法。
The equivalence and uniqueness of the solution of model are demonstrated. Then, MSA algorithm is cooperated with the model.
通过对模型的K-T条件的分析，我们提出了求解模型的简单算法。
We also provide a simple and easy method to solve the model after analysing the K T conditions of the…
通过对模型的等价转换，设计了拉格朗日松弛启发式算法来求解模型。
Lagrange relaxation heuristic algorithm is designed to solve the model by equivalent transformation.
在夹具CAD系统开发过程中，建立了定位误差分析计算的通用求解模型。
A general count model of locating tolerance analysis and calculation was established in the process of exploiting fixture CAD system.
通过分析建立了组合激励的两阶段搏弈模型，求解模型得到了最优报酬组合。
We establish a two-stage model of game in combination of incentive through analysis. We get the excellent combination through solving the model.
通过分析建立了组合激励的两阶段搏弈模型，求解模型得到了最优报酬组合。
We establish a two-stage model of game in combination of incentive through analysis.
采用了时间步长法、等效法以及二者结合的等效时间步长法三种方法求解模型。
The model was solved with the application of different methods, such as time step method, equivalent method and their combination.
受到光束扩散模型和漫射近似理论的启发，提出了一种改进的光传输求解模型。
A modified light diffusion solution model was proposed from a heuristic version of beam spreading (BS) model and diffusion approximation (DA) theory.
通过求解模型获得电站内各台机组在给定日负荷计划下的最佳负荷运行分配方案。
The optimal load distribution scheme for the operation of each unit was obtained under the planned daily load.
设计并进行了集料挤压破碎力实验，并以此建立较为精确的挤压破碎力求解模型；
The rock material compression experiments were carried out and a pressure model relating compression ratio and particle size distribution to compression pressure was presented.
考虑整套试验数据的随机特性，利用极大似然法原理和数学规划法求解模型参数。
The parameters of model are measured by taking into account the stochastic characteristic of entire test data, which is connected with a maximum likelihood method and math programming.
另外，利用等距曲面的概念讨论了空间凸轮机构压力角的概念及其自适应求解模型。
In addition, the conception of press Angle of spatial CAM mechanism is discussed and its mathematics model and self-adaptive arithmetic are given also.
分析了网络安全态势估计问题的本质特征，构造了网络安全态势推理评估的求解模型。
Analyzing the essential characteristic of the network security situation assessment, and the reasoning model is proposed.
ADAMS采用拉格朗日动力学方程，辅以刚性积分算法以及稀疏矩阵技术来求解模型。
ADAMS solves the model by adopting Lagrange dynamics equation and complementing with rigidity integral algorithm and sparse matrix technology.
这里考察了求解无约束总体极小化问题的神经网络方法，提出了一种新的网络求解模型。
Neural network method for solving global unconstrained minimized problems was investigated and a new neural network model was then proposed.
利用粒子群的优化算法，建立侵彻子母弹最佳抛撒高度的求解模型，并进行了仿真计算。
By using Particle Swarm Optimization (PSO), a model was built up for calculating the optimum dispersion height of intrusive submunition dispenser, and mathematical simulation was carried out.
本文选择了免疫算法作为基本算法求解模型，并使用蒙特卡罗方法对风险约束进行转化。
This article chooses the immune algorithm as the basic method to resolve the problem and USES Monte Carlo simulation to transform the risk restriction.
分析传统求解模型及算法研究的局限性，提出对现有模型及算法进行动态集成的研究思路。
The research focused on models and algorithms. The limitation of traditional solution model and algorithm research was analyzed.
将模拟退火算法中的退火策略引入到免疫克隆算法中，设计了求解模型的免疫克隆退火算法。
The immune clone annealing algorithm, which is designed by combining annealing tactic of simulated annealing algorithm and immune clone algorithm, is introduced to solve the proposed bi-level model.
将模拟退火算法中的退火策略引入到免疫克隆算法中，设计了求解模型的免疫克隆退火算法。
The immune clone annealing algorithm, which is designed by combining annealing tactic of simulated annealing algorithm and immune clone algorithm, is introduced to solve the proposed bi-level model.
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