The simulated annealing algorithm, using MATLAB experiment.

神经网络中自适应谐振理论模型实现的C语言源程序！-Neural network adaptive resonance theory model of the C language source code!

中科院的分词动态连接库,不用我说了哈,在国内是大名顶顶哈-CAS-term dynamic link library, I do not have said Kazakhstan, in Kazakhstan after another is Daming

多目标进化算法源代码-more evolutionary algorithm source code

基于神经网络的文字识别系统,它通过遗传算法实现。-Neural Network Based Character Recognition system, which through genetic algorithm.

经过改进的遗传算法的VC源代码。经测试算法有效可行。-improved genetic algorithms VC source. Testing Algorithm effective.

遗传优化神经网络结构，C++源代码-Genetic optimization of neural network architecture, C++ Source code

不确定规划 遗传算法 Goal Programming算法程序- Indefinite plan heredity algorithm Goal Programming algorithm procedure

8。《遗传算法及其应用》，陈国良等编着 人民邮电出版社 2001年第一版 本书系统全面地介绍了遗传算法的基本原理、设计方法及其并行实现，以及它在组合优化、机器学习、图像处理、过程控制、进化神经网络、模糊模式识别和人工生命等方面的应用。 本书可作为高等院校计算机、无线电电子学、自动控制、生物医学工程等有关专业高年级学生或研究生的教材和参考书，也可供从事人工智能、信息处理研究和应用的科技人员学习参考。-8. "Genetic algorithm and its application," Chen Guoliang edited and published with the People"s Post and in 2001 the first book version of the full introduction of the genetic algorithm basic tenets , design methods and parallel implementation, and its portfolio optimization, machine learning, image processing, process control, evolutionary neural networks, Fuzzy Pattern Recognition and Artificial Life, and so on the application. The book can be used as institutions of higher learning computers, radio electronics, automatic control, biomedical engineering, and other professional grade students or graduate teaching and reference materials, are also available in artificial intelligence, information processing and application of information technology to study.

利用遗传算法求解TSP的源代码程序 可以精确求出50城市-The use of genetic algorithm to solve TSP program source code can be precisely calculated 50 cities

提出了基于最小化估计的泛化误差界非优化估计方法。目前大多数的核参数选择方法都是通过极小化了来得到最优参数值，但是求解优化问题的计算代价相当的大，并且不能很好地体现数据的分布特征。本文采用非优化技术，通过极小化泛化误差来优化核及相关参数，由于直接计算最小半径和最大间隔，避免了对优化问题的直接求解，因此可以很好地降低计算代价。并且该方法直接从样本出发，可以很好地体现数据的分布特征，不管数据分布是否均匀都可以适用。给出了基于凸包估计的SVM核选择的模型及实现算法。 -Proposed based on minimizing the estimated generalization error bound of the non-optimal estimation method. Most of the nuclear parameter selection methods are to get the best by minimizing the parameter values, but the computational cost for solving optimization problems is quite large, and can not properly reflect the distribution characteristics of the data. In this paper, the non-optimization technology, by minimizing the generalization error to optimize the nuclear and related parameters, due to the direct calculation of the minimum radius and maximum interval, avoiding the direct solution of the optimization problem, it can very well reduce the computation cost. And that the method directly from the sample one can well reflect the distribution chara