Computational electromagnetics in the genetic algorithm is a better optimization...

本程序为遗传算法示范程序（visaul c++ 源程序）-procedures for the genetic algorithm model procedures (c visaul source)

将遗传算法(GA)与传统SVM算法结合,构造出一种参数最优的进化SVM(GA2SVM),SVM 模型采用径向基函数(RBF)作为核函数，利用格雷码编码方式对SVM算法的模型参数进行遗传编码和优化搜索，将搜索到的优化结果作为SVM 的最终模型参数。-Genetic algorithm (GA) combined with the traditional SVM algorithm, a kind of tectonic evolution of the optimal parameters of SVM (GA2SVM), SVM model using Radial Basis Function (RBF) as kernel function, the use of Gray code encoding algorithm of the SVM model parameters of genetic coding and optimization of search, will search for the optimal results as the final SVM model parameters.

支持向量机(3)svm_light-Support Vector Machines(3):svm_light

微分进化算法DE是1995年由Rainer Storn和Kenneth Price首先提出。DE已被证明在求解过程中具有高效性、收敛性、鲁棒性等优点[5,6] 。它在许多优化问题中都表现出优于自适应模拟退火算法、POS 算法、GA算法的性能。DE利用实数值参数向量作为每一代的种群，它的自参考种群繁殖方案与其他优化算法不同。-DE was first proposed in 1995 by Rainer Storn and Kenneth Price and had been proven that it is efficient, convergent, and robust in the solution process. [5,6] In many optimize questions, its performance surpasses the adaptive simulated annealing algorithm, the POS algorithm, and the GA algorithm. DE gets each generation of population using the real value parameter vector, and the crucial idea of DE is a scheme for generating trial parameter vectors.

数据挖掘经典算法遗传算法的C++实现源码-Classical data mining algorithm for genetic algorithm C++ Realize source

基于梯度训练方法的rbf神经网络实现，采用随机训练及测试数据-Gradient-based training methods of rbf neural network, using a random training and test data

人工智能实验 -experimental AI Artificial Intelligence Experiment

变色龙层次聚类算法，利用动态模型的层次聚类算法-chameleon hierarchical clustering algorithm, using a dynamic model of hierarchical clustering algorithm

模式识别中的K－均值算法演示-pattern recognition, the K-means algorithm demo

基于bp人工智能的图像识别的技术，配套源代码-bp artificial intelligence-based image recognition technology and supporting source code