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经典Apriori算法的优化，并在商场消费者消费数据集上进行测试，挖掘频繁模式-Optimization of classical Apriori algorithm, and tested in store consumer data sets, frequent pattern mining
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对无约束的优化模型利用BFGS算法进行求解-For unconstrained optimization model uses BFGS algorithm to solve
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对三次样条函数的模型利用BFGS算法进行优化求解-Cubic spline function model using BFGS algorithm optimization solution
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对k-means算法的优化，通过优化初始聚类中心的选择-The optimization of K-means algorithm by improving the selection of initial clustering centers
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社会网络影响最大化问题中的模拟退火算法，是格局爬上算法的一种优化算法，用于社会网络分析.-Social network influence maximization problem in simulated annealing algorithm, is a kind of pattern climb algorithm optimization algorithm, for social network analysis.
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人工鱼群算法的实现代码，有效处理优化寻优问题，比遗传算法、PSO具有更好的优化效果-Artificial fish swarm algorithm code to deal effectively optimize the optimization problem, with better optimization results than the genetic algorithm
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针对工业控制中常用的PID控制器参数整定困难的问题,提出一种基于人工蜂群算法的参数整定方法。将PID控制器待整定参数看作蜜源,利用蜂群特有的角色转变机制搜索优质的参数组合 选取绝对误差矩积分性能指标作为参数寻优的目标函数。仿真实验结果表明,所采用的算法能够提高控制系统的动态性能,增强系统的快速性和稳定性,适用于PID控制器的自整定。
-For industrial control commonly used in PID controller tuning difficult problem
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离散粒子群算法。粒子群算法原来只能处理连续变量，算法进行了改进，可以处理离散变量-Discrete particle swarm optimization algorithm, particle swarm optimization algorithm can only deal with continuous variables, the algorithm is improved, can handle discrete variables
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一维及二维数据粒子算法寻优,包括1）二维粒子算法参数寻优-替代网格寻优；2）一维数据粒子算法寻优（极值）。-
One dimensional and two dimensional data particle algorithm optimization, including 1) two dimensional particle algorithm parameter optimization- alternative grid optimization 2) one dimens
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genetic algorithm for optimization and bee colony algorithm accompanied by fuzzy c means clustering .
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运用种群遗传算法优化BP神经网络的权值和阀值-The use of genetic algorithm optimization BP neural network weights and thresholds
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Logistic回归主要目的是寻找一个非线性sigmoid的最佳拟合参数，采用梯度上升算法可以达到局部的最优化-The main purpose of Logistic regression is to find the best fitting parameters of a nonlinear sigmoid, and the gradient ascent algorithm can be used to achieve the local optimization.
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支持向量机是最常用的一种分类器，它通过求解一个二次优化问题来最大化分类间隔，本例采用的SMO算法，可以大大优化运行-Support vector machine is the most commonly used classifier, it can be used to solve a two optimization problem to maximize the classification interval, this example uses the SMO algorithm, ca
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建立LibSVM预测模型，基于网格算法、粒子群算法、遗传算法优化了模型参数，并由最终模型预测了给定切削参数下零件的粗糙度等级。-Establish LibSVM prediction model, grid-based algorithm, particle swarm optimization, genetic algorithm to optimize the parameters of the model, the final model prediction given by the c
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利用退火算法解决最优化问题，如最多带物品的质量为M，每件物品的质量为mi，价格为yi，怎么做才能带走价值最多的物品？(Annealing algorithm to solve the optimization problem, such as the maximum quality of goods with M, the quality of each item is Mi, the price is Yi, how to do to take away the most valuable i
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K-Means是聚类算法中的一种，其中K表示类别数，Means表示均值。顾名思义K-Means是一种通过均值对数据点进行聚类的算法。K-Means算法通过预先设定的K值及每个类别的初始质心对相似的数据点进行划分。并通过划分后的均值迭代优化获得最优的聚类结果。(K-Means is one of the clustering algorithms, in which K represents the number of classes, and Means means the mean. As t
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用遗传算法优化支持向量回归机C、g、p参数(Optimization of C, G, P parameters of support vector regression machine by genetic algorithm)
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