In this paper, two sub-swarms substituting particle swarm optimization algorithm (TSSPSO) is proposed. The algorithm parameters are analyzed and the iteration equations are amended.
提出一种两群替代微粒群优化算法(TSSPSO)，并对算法参数进行分析和对算法方程进行修正。
Although a few researches have discussed the optimization problem under network coding scenario, their aim is to seek minimum-cost multicast sub-graph.
虽然也有不少研究关注网络编码应用中的优化问题，但都侧重于求解最小代价多播子图问题。
Aiming at problem that Particle Swarm Optimization (PSO) algorithm falls into local optimum easily, this paper presents a PSO algorithm based on sub-region.
针对粒子群优化(PSO)算法在寻优时容易陷入局部最优的不足，提出一种基于子区域的PSO算法。
The main idea of integrated strategies is to make the original problems be a series of sub- problems and choose appropriate method for optimization.
集成策略的基本思想是把原问题分解为一系列的子问题，并采用合适的方法优化之。
For the multidisciplinary design optimization (MDO) of spacecraft with sub-vehicles, system mission requirements and disciplinary coupling relations are analyzed.
针对带子星航天器总体参数多学科设计优化（MDO）问题，进行系统任务分析和学科耦合关系分析。
HDO divides the integrated optimization of composite wing structures into two sub-problems that are easy to be solved: upper level optimization and lower level optimization.
它将复合材料翼面结构综合优化设计问题分解成两个易于求解的子问题：顶层优化设计和底层优化设计。
On the basis of analyzing the particle swarm optimization and introducing the idea of sub-swarms, a particle swarm optimization algorithm with dynamic sub-swarms (DPSO) is proposed.
在分析基本微粒群优化算法的基础上，引进分群思想，提出了一种动态分群的微粒群优化算法(DPSO)。
In this paper, a composite domain topology optimization (CDTO) method is proposed to control the distribution of different amount of material in the design sub-domain of structure.
提出一种复合域拓扑优化方法以控制结构设计子域的不同材料数量分布。
Basing on particle swarm optimization, this paper gives the algorithm on coalition formation and the sub-task allocation in the agent-based distributed measurement system.
根据粒子群优化算法的基本原理，提出基于粒子群优化算法的智能体测试系统联盟形成以及测试子任务优化分配算法。
The corrective control problem was decomposed into a nonlinear power flow and linear sensitivity computation sub-problem and a sensitivity-based linear programming optimization control sub-problem.
该算法基于连续线性规划技术，将安全校正问题分解为非线性潮流和线性控制灵敏度计算子问题以及基于灵敏度的线性规划控制子问题。
Some parameters such as the depth of interleaving and selection of sub-channels can be planned depending on the reality to achieve the optimization.
上述为方案的大体流程，其中具体实现参数，比如交织深度、基准信号对应的信道的选取等一些参数要依具体应用而定，使系统性能达到最佳。
Some parameters such as the depth of interleaving and selection of sub-channels can be planned depending on the reality to achieve the optimization.
上述为方案的大体流程，其中具体实现参数，比如交织深度、基准信号对应的信道的选取等一些参数要依具体应用而定，使系统性能达到最佳。
应用推荐