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粒子群程序,是一种有效的优化算法,用于控制-Particle swarm procedure is an effective optimization algorithm is used to control
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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
用粒子群算法优化模型中的三个主要参数：C1、C2、sigma-The file is in particle swarm optimization parameters of support vector machine model matlab code for support vector machine model designed for use with
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研究基于粒子群算法控制系统PID参数优化设计方法以及对PID控制的改进。- study the optimal design of PID parameter of the control system based on Particle Swarm Optimization and find a way to improve the PID control.
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mtlab粒子群优化模糊RBF神经网络整定PID控制-mtlab Particle Swarm Optimization Fuzzy RBF neural network PID control tuning
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PSO PID 粒子群优化的最优控制器 用于交通流量控制
PSO PID 粒子群优化的最优控制器 用于交通流量控制-Particle Swarm Optimization PSO PID controller for optimal traffic flow control
Particle Swarm Optimization PSO PID controller for optimal traffic flow control
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基于粒子群算法的PID控制算法MATLAB源程序-PID control algorithm based on particle swarm optimization algorithm
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Artificial Bee Colony (ABC) is one of the most recently defined algorithms by Dervis Karaboga in 2005, motivated by the intelligent behavior of honey bees. It is as simple as Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithm
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基于粒子群优化的预测算法，用于锅炉汽温的控制-Prediction algorithm based on particle swarm optimization for boiler steam temperature control
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The performance of fuzzy logic (FLC)control optimized by particle swarm optimization (PSO) for semi-active suspension system using magneto-rheological (MR) damper . MR damper is an intelligent damper filled with particle magnetic polarizable and susp
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基于粒子群算法的pid控制，MATLAB仿真-Based on Particle Swarm Optimization pid control, MATLAB simulation
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本程序在matlab环境下，基于粒子群算法对pid控制器进行优化控制,从而完成性能更优-The program in matlab environment, based on particle swarm optimization algorithm pid controller to control, thus completing the better performance
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通过改进获得一种量子行为的粒子群优化算法，并将该算法应用于某机组的燃烧控制系统的建模研究，获得不同工况下的传递函数形式的系统模型。-Obtain a quantum behavior improved particle swarm optimization algorithm, and the algorithm is applied to the model building of a unit combustion control system, access to system trans
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粒子群算法实现铁路电能质量控制系统容量优化matlba GUI界面-Particle swarm optimization (pso) algorithm to realize railway capacity optimization GUI interface power quality control system
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粒子群优化算法(PSO：Particle swarm optimization) 是一种进化计算技术（evolutionary computation）。
源于对鸟群捕食的行为研究。粒子群优化算法的基本思想：是通过群体中个体之间的协作和信息共享来寻找最优解．
PSO的优势：在于简单容易实现并且没有许多参数的调节。目前已被广泛应用于函数优化、神经网络训练、模糊系统控制以及其他遗传算法的应用领域。(The particle swarm optimization (PSO:Part
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利用标准粒子群算法优化PID参数，用以控制直流电机模型(The standard particle swarm optimization (PSO) algorithm is used to optimize the PID parameters to control the DC motor model)
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针对自治水下机器人(AUV)的路径规划问题进行了研究,依据模糊控制规则,提出了一种基于粒子群优化(PSO)的模糊路径规划算法(The path planning problem of autonomous underwater vehicle (AUV) is studied. According to the fuzzy control rules, a fuzzy path planning algorithm based on particle swarm optimization (PS
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基于粒子群算法求解低速车辆模型的非线性模型预测控制问题(The nonlinear model predictive control problem of low-speed vehicle is solved based on particle swarm optimization (pso))
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粒子群算法（PSO）整定pid控制参数，比传统Z-N整定方法要好，内附matlab程序与simulink模型(Particle swarm optimization (PSO) is better than traditional Z-N tuning method in tuning PID control parameters. It includes matlab program and Simulink model.)
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