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1)  hybrid search(HS)
禁忌粒子群优化
2)  TS-PSO algorithm
禁忌粒子群优化算法
3)  particle swarm optimization(PSO)
粒子群优化
1.
With the introduction of punishment function and the appropriate modification of objective function,a sintering blending optimization algorithm is proposed,which takes full advantage of the global search ability of particle swarm optimization(PSO) algorithm and the local search ability of conjugate gradient algorithm with constraints.
在引入惩罚函数和对目标函数进行适当修改的前提下,充分利用粒子群优化算法的全局搜索能力和约束条件下共轭梯度法的局部搜索能力,设计了烧结配料优化算法。
2.
In order to solve the problems of low-precision and slow control of the traditional algorithms in the pattern recognition and control of flatness,the neural network trained by hybrid algorithms of particle swarm optimization(PSO) and back propagation(BP)is introduced.
为了解决传统的板形识别与控制中的识别精度低,控制速度慢等问题,将粒子群优化(particle swarm optimization,PSO)算法和误差反传递(back propagation,BP)算法混合训练的PSO-BP网络引入到板形的识别与控制中。
3.
HPSO introduces evolutionary algorithm into particle swarm optimization(PSO),thus can get higher precision and faster convergence spe.
由于电力负荷内在的非线性特性,传统基于梯度搜索的参数辨识技术可能陷入局部最优,影响了预测精度,故提出了混合进化和粒子群优化算法。
4)  particle swarm optimization
粒子群优化
1.
Multi-objective model of tolerance design and its solution with particle swarm optimization algorithm;
公差设计多目标模型及其粒子群优化算法研究
2.
Application of immune particle swarm optimization to job-shop scheduling problem;
免疫粒子群优化算法在车间作业调度中的应用
3.
Bayer material balance computation based on improved particle swarm optimization algorithm;
基于改进粒子群优化技术的拜耳法物料平衡计算
5)  PSO
粒子群优化
1.
Transmission Network Optimization Planning Based on Hybrid PSO;
基于混合粒子群优化的电网优化规划
2.
PSO-Based Optimization of Signal Timing and Simulation for Isolated Intersection;
基于粒子群优化的单交叉口信号控制与仿真
3.
An optimal phase-factor selection algorithm for PTS based on PSO in OFDM;
OFDM中基于粒子群优化的PTS相位因子优选算法
6)  Particle swarm optimization (PSO)
粒子群优化
1.
Particle swarm optimization (PSO) and filter preprocessing based on hamming window is used to search the registration parameters.
针对互信息在多模态医学图像配准中的局部极值问题,利用海明窗(Hamming窗)进行滤波预处理,并采用粒子群优化(Particle swarm optimization,PSO)方法搜索配准参数。
2.
The particle swarm optimization (PSO) algorithm is used to obtain the optimal solution to the minimization problem (i.
利用粒子群优化(PSO)算法在整个参数空间内并行搜索获得极小值优化问题的最优解(Wiener模型的最优估计),通过对粒子的迭代轨迹进行分析,改进了PSO算法中惯性权重和学习因子的选择。
3.
Due to the disadvantages of the canonical Particle Swarm Optimization (PSO), a new adaptive particle swarm optimization algorithm based on Sigmoid inertia weight was proposed.
针对粒子群优化算法存在的缺点,提出了基于Sigmoid惯性权值的自适应粒子群优化算法。
补充资料:颜料β粒子群
分子式:
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性质:系指由多个原级粒子或二次粒子或它们两者通过比较弱的物理力,以粒子与粒子的棱或角相接触而形成的疏松的集合体,又称颜料三次粒子(pigment tertiary particle),也称颜料β粒子群(β-particle cluster of pigment)。由于粒子间的结合力弱,可通过颜料分散过程使其分离开,故它本身不能在颜料最终应用系统中作为一个实体而存在。是由颜料在制造和贮存过程中产生的。附聚体(agglomerate)与聚集体(aggregate),絮凝体(flocculate)不可混淆。

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