差分进化算法的一篇全国优秀硕士论文，目前国内对此的研究还处于初步阶段...

以黎曼几何为理论依据，基于S.Amari的修正核函数思想提出了两种新的保角变换，用其对核函数进行数据依赖性改进，进一步提高支持向量机分类器泛化能力。以人工非线性分类问题 为对象进行研究，仿真实验结果表明采用新保角映射可以快速显著地改善分类器泛化性能，而且能大幅度地减少支持向量的数目。-Two novel conformal transformations were proposed based on the Riemannian geometry theory and S.Amari’sidea.And the kernel function was modified by the transformation in a data-dependent way.Our experimental results for theartificial nonlinear data set show that the generalization performance of support vector machines classifier is improvedremarkably and the number of support vectors is decreased greatly.

清华大学不确定规划教材中的模糊模拟算法1-Tsinghua University, teaching in the planning uncertainty simulation algorithm fuzzy one

BP神经网络分类器C程序-BP neural network classifiers C Program

用MATLAB编写的支持向量机，实现了线性可分与线性不可分的情况，还有非线性支持向量机，里面部分常用的核函数。-Prepared using MATLAB support vector machine, to achieve a linearly separable and linear indivisible, it is still non-linear support vector machine, which part of the kernel function used.

apriori算法是数据挖据中的经典关联规则挖掘算法，是由aggwal最早提出来的-apriori algorithm is data-dug, according to the classical association rule mining algorithm is put forward as early as aggwal

利用遗传算法对图像进行分类处理，包括遗传的思想和实现，以及在图像方面的应用。-The use of genetic algorithm to classify the image processing, including genetic and realization of the idea, as well as the application of the image.

开发环境：Visual C++ .net2003 功能介绍：神经网络算法实验；分Console版本和MFC版本；主要用来求解TSP问题。-Development Environment: Visual C++. Net2003 function introduction: neural network algorithm experiments sub-Console version and MFC version mainly used to solve the TSP problem.

这是我自己做的改进的遗传算法，主要是克服遗传算法的早熟问题-This is what I want done to improve the genetic algorithm, which is aimed at overcoming the genetic algorithm early problems

利用遗传算法求最小值，程序中求得是表达式x1*x1+x2*x2+x3*x3再-2~2上的最小值，以及对应的x值，算法中使用二进制编码，交叉采用不同交叉和优势交叉，变异也分两种，不用变异和优势变异-using genetic algorithms for the minimum, procedures to seek expressions x1 x1 x2*** x2 x3 x3 another 2 ~ 2 on the minimum, and the corresponding value of x, algorithm using binary encoding, using different cross-cross and advantages of crossover and mutation at the two without variation and variation advantage

特别是在题库管理模块中对自动组卷功能常用的算法（包括随机选取法、回溯试探法和遗传算法）进行了比较。对于较流行的验证码技术也给出了具体实现。-particularly in the examination management module to automatically making up the algorithm commonly used functions (including random selection method, Retrospective testing and genetic algorithm) were compared. For more popular authentication code technology has provided a concrete realization.