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4下载:
这个是我自己编写的基于混沌自适应粒子群优化支持向量机用于分类的matlab程序,本程序以心脏病的诊断为例,得出了非常好的效果!主要贡献在于解决了支持向量机参数人为选取随意性大且效果好坏不稳定的难题!-This is what I have written based on adaptive chaotic particle swarm optimization of support vector machine for classification of matlab procedures, t
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这是一个混沌粒子群算法,请大家多多指教啊!-This is a chaotic particle swarm optimization, please exhibitions ah!
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使用Scilab编写的粒子群算法,例子比较简单,无混沌搜索-Scilab prepared using particle swarm optimization, for example, relatively simple, non-chaotic search
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This program is an M-file of Chaotic version of Particle Swarm Optimization method.
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混沌的粒子群算法,求解无约束优化问题,可以保持个体多样性-Chaotic particle swarm algorithm for solving unconstrained optimization problems, can maintain the diversity of individual
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基于混沌粒子群与模拟退火优化算法的最小二乘支持向量机参数自选择方法-Based on Chaotic Particle Swarm Optimization and Simulated Annealing least squares support vector machine parameter self-selection method
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粒子群优化算法是一种进化优化技术,源于对鸟群扑食的行为,是一种基于迭代的优化工具。此文件提供了基本粒子群算法、带压缩因子的粒子群算法、二阶粒子群算法、二阶振荡粒子群算法、权重改进的粒子群算法、混沌粒子群算法、基于杂交的粒子群算法、基于模拟退火的粒子群算法的MATLAB源代码。-PSO is an evolutionary optimization technique, derived from the behavior of the birds of prey, is based on iter
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一种混沌粒子群嵌入优化算法及其仿真Embedded in a chaotic particle swarm optimization algorithm and simulation-Embedded in a chaotic particle swarm optimization algorithm and simulation
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基于混沌的文化粒子群算法有很好的计算精度可以计算多维方程-Chaotic particle swarm optimization and cultural accuracy are very good multi-dimensional equations can be calculated
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针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷
入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。
该方法考虑了图像中像素点灰度 邻域灰度均值对作为阈值对图像进行分割 利用混沌运
动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜
索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索
时间, 提高了收敛率
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针对工程优化设计问题,提出了基于混沌粒子群算法的工程约束优化问题求解方法。CPSO算法利用混沌搜
索的全局遍历性、随机性和规律性等特点, 引导粒子在全局范围内搜索, 从而克服了传统粒子群算法早熟收敛的缺点。
该算法以种群适应度方差作为粒子群优化算法早熟收敛的判据, 并用惩罚函数法处理违法约束的粒子, 当基本粒子群算
法陷入早熟时, 随机选择粒子群中的部分粒子实施混沌搜索, 直至满足迭代收敛条件为止。CPSO算法能提高种群的多
样性和粒子搜索的遍历性, 从而有效提高了PSO算法的收
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文件包括带压缩因子的粒子群算法,权重改进的粒子群算法,自适应权重法,随机权重法,变学习因子的粒子群算法,异步变化的学习因子,二阶粒子群算法,二阶振荡粒子群算法,混沌粒子群算法,混合粒子群算法,杂交粒子群算法,模拟退火算法-File with compression factor of the particle swarm algorithm, the weight to improve particle swarm optimization, adaptive weighting method,
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混沌粒子群寻优算法和各种常见的混沌吸引子程序-Chaotic particle swarm optimization algorithm, and a variety of common chaotic attractor subroutine
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该程序是混沌粒子群苏算法的代码,修改参数就可以用。-The program is chaotic particle swarm the Su algorithm the code can modify the parameters.
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混沌粒子群优化调整adrc参数 PSO_ADRC.m chaos.m-The adjust the chaotic particle swarm optimization adrc parameters
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混沌粒子群优化(CPSO, Chaos Particle Swarm Optimization)算法融合了PSO算法的快收敛和CO算法的遍历随机等特点,在PSO算法每一代挑选出的最优解附近的区域里,用混沌算法进一步搜索,防止其陷入局部最优值,从而改进了PSO算法的不足,成为一种高效的优化算法。-Chaotic Particle Swarm Optimization (CPSO, Chaos Particle Swarm Optimization) algorithm combines the f
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Cockroach Swarm Optimization
a new bionic algorithm, entitled
Cockroach Swarm Optimization (CSO), that is inspired by the
social behavior of cockroaches. We construct some models by
imitating the foraging behaviors of cockroach, and describe
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基于混沌粒子群与模拟退火优化算法的最小二乘支持向量机参数自选择方法-Based on Chaotic Particle Swarm Optimization Algorithm and Simulated Annealing least squares support vector machine parameters from selection method
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针对粒子群优化算法稳定性较差和易陷入局部极值的缺点,论文提出了一种新颖的混沌粒子群优化算法。-Particle swarm optimization for the poor stability and ease of getting into local extremum shortcomings, the paper proposes a novel chaotic particle swarm optimization algorithm.
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针对传统粒子群算法初期收敛较快,而在后期容易陷入早熟、局部最优的特点,提出了一种新的混沌粒子群优化算法-For early traditional PSO algorithm converges faster and easier in the late fall early, optimal local characteristics, we propose a new chaotic particle swarm optimization
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