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swarm相关的网络例句

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A modified Particle Swarm Optimization algorithm is proposed and used to optimize the sidelobe level of plane arrays, in which special techniques as global best perturbation and jumped inertia weight strategy are adopted. The PSO algorithm is also used to select a better combination of optimal parameters for itself.

摘要该文运用一种改进的粒子群优化算法对不等幅激励的矩形平面阵列天线的最大旁瓣电平进行了优化,采用对全局最优粒子微扰和跳变的惯性权重策略,并使用粒子群算法本身对参数组合进行了优化选择。

Based on particle swarm optimization and fuzzy linear proximal support vector machine, a rotating machinery fault diagnosis method was proposed.

研究了粒子群优化改进的模糊线性PSVM在旋转机械故障诊断的应用。

Particle swarm optimization and linear matrix inequality were used for the design of input-constrained nonlinear predictive controller .

将微粒群算法与线性矩阵不等式用于输入受限非线性预测控制器的设计,提出了基于PSO与LMI联合优化的非线性预测控制算法。

To study the performance of the algorithm, it is tested with a set of 5 benchmark functions and compared with the linear decrease weight particle swarm optimization algorithm.

为了评价其性能,选取了5个基准函数进行测试,并与惯性权重线性递减的粒子群优化算法作了比较。

In order to solve the problem of knowledge acquisition in liquid propellant engine fault diagnosis, a method based on immune chaos particle swarm optimization was proposed.

为解决液体发动机故障诊断中知识获取的瓶颈问题,提出了一种基于免疫混沌改进粒子群优化算法的知识获取方法。

All the creatures that swarm on the ground are loathsome and shall not be eaten.

凡地上的爬虫,都是当憎恶的,都不可吃。

Traditional Swarm Optimization algorithm can not choose parameters according to practical problem,and plunge into the local extremum point easily at the end of the searching.

针对传统粒子群优化算法不能根据实际问题自行选择参数,搜索后期容易陷入局部最优的缺点,提出了一种基于随机摄动的复合粒子群优化算法。

A hybrid particle swarm optimization algorithm based on the chaos search is proposed. It can not only overcome the disadvantage of easily getting into the local extremum in the later evolution period, but also keep the rapidity of the previous period.

所提出的算法将粒子群优化算法和混沌算法相结合,既摆脱了算法搜索后期易陷入局部极值点的缺点,同时又保持了前期搜索的快速性。

The traditional training methods of Gaussian Mixture Model are sensitive to the initial model parameters, which often leads to a local optimal parameter in practice. To resolve this problem, a new GMM optimization method was proposed based on Particle Swarm Optimization.

为了解决传统高斯混合模型对初值敏感,在实际训练中极易得到局部最优参数的问题,提出了一种采用微粒群算法优化GMM参数的新方法。

Lovejoy adds that high-altitude winds would have been essential for the swarm's flight.

拉夫卓伊指出,当时的高空气流对蝗虫群的飞行就至关重要。

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