为了提高优化性能，将粒子群算法和模拟退火算法结合，得到了粒子群-模拟退火混合调度算法。
In order to improve its performance, the paper puts forward a hybrid algorithm which blends the PSO algorithm and simulated annealing algorithm.
提出了一种新颖的基于粒子群优化和多级检测的混合算法的多用户检测器。
A novel hybrid algorithm approach that employs a particle swarm optimization (PSO) and a multistage detection for the multiuser detection problem (PSOMSD) is proposed.
与其他混合最优化算法不同的是，该算法没有破坏粒子群和遗传算法的独立性，而是仅通过全局最优样本把两个算法结合在一起。
It selects the optimaler number as a global optimum at every circulation, which makes its result be better than both PSO and GA, then improves the overall performance of the algorithm.
在此基础上，进一步提出了混合粒子群算法和速度变异粒子群算法两种改进算法提高优化性能。
For improving the predicting results, two improved PSO algorithm are presented also in this paper: Velocity Mutation PSO and hybrid PSO.
基于粒子群算法运用随机模拟和模糊模拟相结合的技术，给出了一种求解该规划模型的混合智能算法。
Desgined a mixed intelligent arithmetic by using the technique of combing the stochastic simulation with fuzzy simulation and particle swarm optimization algorithm to solve this kind of problems.
针对模糊c均值算法与粒子群算法的不足，提出了一种基于粒子群算法和模糊c—均值算法的混合聚类算法。
To avoid the shortcomings of FCM and Particle Swarm Optimization algorithm, new hybrid clustering algorithm based on PSO and FCM algorithm is proposed.
文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合，提出了两种混合量子进化算法。
Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid Quantum Evolutionary algorithms (QEA) based on combining QEA with Particle Swarm optimization (PSO).
为了提高粒子群算法的寻优速度和寻优精度，提出一种改进的PSO混合算法。
This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm.
为了提高粒子群算法的寻优速度和寻优精度，提出一种改进的PSO混合算法。
This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm.
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