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algorithm相关的网络例句

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In the algorithm designed here, polygon-fill algorithm and "Painter Algorithm" are used to display 3-D isoline," Windup Storage" method to balance computer processing load,"Associative Fan in" method to conflate results, and "Run Length Compression" method to save network communication time.

根据等值线数据量随其属性值而变化的特点,设计了采用"卷帘存储法"实现负载平衡的等值线三维显示的并行算法;采用"结合扇入法"实现结果合并,并采用"运行长度压缩法"以缩短网络通讯时间。

In the algorithm designed here, polygon-fill algorithm and "Painter Algorithm" are used to display 3-D isoline,"Windup Storage" method to balance computer processing load,"Associative Fan in" method to conflate results, and "Run Length Compression" method to save network communication time.

运用多边形填充和"画家算法",实现了等值线三维显示;根据等值线数据量随其属性值而变化的特点,设计了采用"卷帘存储法"实现负载平衡的等值线三维显示的并行算法;采用"结合扇入法"实现结果合并,并采用"运行长度压缩法"以缩短网络通讯时间。

The essential features of the algorithm are as follows: A kernel modification algorithm is constructed according to the conformal mapping of information geometry and the modified kernel function is subsequently used to train the classification algorithm in support vector data description.

该算法的核心思想为:根据信息几何中保角映射的方法构造数据驱动的核函数修正算法,然后再利用修正的核函数训练支持向量数据描述分类算法。

The examples indicate that the algorithm has strong pertinence and high efficiency, hi the discrete variable optimization, the problem is solved in the relative quotient method On the base of analyzing the relative quotient method, the conjugate gradient direction is used to modify the old search directions, the iterative matrix of the algorithm, and the method to resolve the discrete variable optimization, the relative conjugate difference quotient algorithm is presented.

离散变量优化算法是从相对差商法开始的,在详细分析相对差上法的基础上,用共轭梯度方向修正原有的搜索方向,并对算法的迭代矩阵进行相关的修改,最终形成一种用于求解离散变量优化问题的RCDQ法。

Optimization solution algorithm is the most important in topology optimization.Algorithms fit for discrete structure and continuum structure are all investigated. Thecharacteristic and different using limit of both optimization criteria method andmathematics programming method are all analyzed in this paper. OC algorithm and theseries MMA algorithm based on SIMP approach are deducedand used for the topology optimization problem of continuum structure.

优化求解算法是拓扑优化问题求解的核心和关键,本文系统分析了适用于离散结构和连续体结构优化的优化求解算法,重点讨论了 OC 算法和 MP 算法,分析比较了不同算法的特点和适用范围,推导了基于 SIMP 理论的优化准则法和 MMA 系列算法,并将MMA 系列算法应用于连续体结构拓扑优化问题的求解。

Thecharacteristic and different using limit of both optimization criteria method andmathematics programming method are all analyzed in this paper. OC algorithm and theseries MMA algorithm based on SIMP approach are deducedand used for the topology optimization problem of continuum structure. MMA algorithm hasa bad convergence but it has a high computational efficiency, while GCMMA is excellent onconvergence and stability with bad calculation efficiency.

优化求解算法是拓扑优化问题求解的核心和关键,本文系统分析了适用于离散结构和连续体结构优化的优化求解算法,重点讨论了 OC 算法和 MP 算法,分析比较了不同算法的特点和适用范围,推导了基于 SIMP 理论的优化准则法和 MMA 系列算法,并将MMA 系列算法应用于连续体结构拓扑优化问题的求解。

Moreover, the algorithm can converge to the desired userunder discretional initial conditions, and the performance of convergence andsteady-state behavior of the algorithm are more better than that of otheralgorithms.Therfore the proposed algorithm is a practical and valuable method in thefuture.

由于其步长的自适应变化,使得它在多径衰落信道中,依然具有较好的性能,而且在任意初始条件下,都能够正确收敛到目标用户,收敛速度更快,稳态性能更好,具有一定的实用性。

PSO is a population-based optimization algorithm, which mimics the social behavior of animals in a flock. It makes use of individual and group memory to update each particle position allowing global and local search optimization. The objective function considered was the total weight of the structure subjected to stresses, displacements and forces constraints. The effects of the parameters were investigated as well and such combination of tuning parameters promote a better global search behavior avoiding premature convergence while rapidly converging to the optimal solution. Results showed the effectiveness of the proposed method by comparing with ANSYS Design Optimization Tool (zero-order method). The PSO with the tuning parameters makes it an ideal method for offshore wind turbines foundations optimization tasks.(2) A reliability analysis method for pile foundation bearing axial loads based PSOThe performance function of pile foundation's axially bearing capacity sometimes is nonlinear and complex, on the basis of geometric meaning of structural reliability index, an optimum model with PSO for structural reliability analysis under arbitrary random variables was established, The PSO algorithm is very efficient to solve global optimization problemsIts use in structural reliability field presents not only the advantage of its facility of implementation, but also the possibility to obtain the design point and the failure probability with a good accuracy. In addition, PSO is a zero order algorithm, for no derivative is necessary for its implementation.

本文的研究针对桩式海上风机基础结构的特点,在国内外有关研究成果的基础上对海上风机基础结构优化设计理论和可靠度方法一些相关问题进行了较为深入的研究,具体做了以下几个方面的工作:(1)基于粒子群优化的桩式海上风机基础确定性优化设计方法桩式海上风机基础的优化设计是一个复杂的、非线性约束的优化问题,针对传统的基于梯度信息的优化方法在处理非线性问题中易陷入局部最优解的问题,本文将一种耦合惩罚函数的PSO算法引入到海上风机基础结构概念设计中,PSO算法是从群体动物聚集觅食这一活动中受到启发而发展的,该算法利用个体和群体的信息共享不断改进自身的位置从而进行局部和全局最优搜索,本文中以桩和三脚架连接段直径及壁厚为设计变量,以基础总重量作为优化的目标函数,在给定的约束条件下建立了三脚架基础优化数学模型,另外本文还研究了PSO参数变化对结果的影响,协调的参数组合可以避免陷入早熟收敛而能够快速的获得全局的最优解,通过与ANSYS优化模块的计算结果比较验证了该方法的有效性,本方法为海上风机基础的确定性设计提供了一条有效的途径。

In accordance with discrete, non-symmetry and time-delay feedback neural networks, we provide some theoretical criteria to judge the stability for designing the networks. On continuous feedback networks, we built an algorithm to estimate the convergence region. On the HNN feedback networks, an effective optimization algorithm based on the annealing strategy and the chaotic neural network is presented, and some disciplinary conclusions are provided to guide the selection of parameters. Simulation results on benchmark problems demonstrate that the performances of our algorithm are distinctly superior to those of the classic HNN based on gradient descend and stochastic optimization methods based on probabilistic distribution.

针对离散、非对称和时延等三种类型的动态反馈网络,给出了可用于网络设计的稳定性判别准则;针对连续动态反馈网络,建立了其收敛域估计的一个算法;针对以HNN模型描述的动态反馈网络,基于退火策略和混沌神经网络提出了一种高效的优化算法,建立了可用于指导参数选择的一些规律性结论,对典型算例的仿真研究显示,改进算法在各类性能上相对基于梯度下降的传统HNN模型和基于概率分布的随机优化算法,具有明显的优越性。

Compared with traditional DFS algorithm and simulated annealing algorithm, the proposed algorithm possesses better convergency and high convergence rate.

该算法克服了DFS算法收敛性差和模拟退火算法收敛速度慢的缺点。

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