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基于粒子群算法的高速公路速度可变控制。可以用来仿真-Based on particle swarm optimization variable speed control of the highway. Simulation can be used to
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该文件为粒子群算法优化支持向量机模型参数的matlab代码 支持向量机模型为专门用于处理不平衡数据的成本控制型支持向量机模型-Matlab code of the file support vector machine model parameters for particle swarm optimization support vector machine model for cost control, support vector machine model for dealing wit
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RLS Control of a linear system.
Abstract This paper proposes a novel method for
controlling the convergence rate of a particle swarm
optimization algorithm using fractional calculus (FC)
concepts. The optimization is tested for several well-
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智能算法中的粒子群算法来控制PID控制器里的参数来调节单位阶跃响应，效果不错，大家可以参考-Intelligent algorithm of particle swarm optimization (pso) algorithm to control the parameters in the PID controller to adjust the unit step response, the effect is good, you can reference
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该算法是以粒子群中粒子的收敛特性为基础,依据量子物理理论提出的,改变了传统粒子群算法的搜索策略,可使粒子在整个可行解空间中搜索寻求全局最优解。同时该算法的进化方程中不需要速度向量,而且进化方程的形式更简单,参数较少且容易控制。对两个算例进行仿真测试,证实该算法可有效解决经济负荷分配问题 性能对比显示,该算法求得的解优于已有的改进粒子群算法及其它优化算法所求得的解。-The algorithm is based on convergence particle swarm particle basi
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PSO粒子群优化的PID参数，通过matlab平台C语言来编写，达到优化控制的目的(PSO particle swarm optimization PID parameters, through the MATLAB platform C language to write, to achieve the purpose of optimization control)
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粒子群寻优，根据现场数据寻找合适的模型参数，为了后续控制(Particle swarm optimization, according to the field data to find the appropriate model parameters, for the follow-up control)
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