线性判别分类器在虹膜数据集上的应用

非线性规划中求解无约束问题中的一个有效方法--模矢法(步长加速法),并用图表示出来步骤.-Nonlinear Programming Solution unconstrained problem of an effective method-- vector mode (step acceleration), and using map out steps.

介绍了蚁群算法解决具体问题的优化算法，实践证明效果很好-on the ant colony algorithm for solving specific problems Optimization Practice has proved very effective

TSP问题是组合优化中的经典问题。其解决方法有局部优化方法和一些启发式算法,局部搜索方法充分考虑问题 的邻域结构,遗传算法有很好的全局搜索能力,memetic算法把遗传算法和局部优化算法相结合,试验结果证明,能很好地解 决TSP问题。-TSP problem is a classic combinatorial optimization problem. Its solution has a number of local optimization methods and heuristic algorithms, local search methods take full account of the issue of neighborhood structure, genetic algorithm has good ability of global search, memetic algorithm for the genetic algorithm and local optimization algorithm combining test results proved that well positioned to solve the TSP problem.

RBF程序，可实现函数拟合，本人已经亲自调试过，效果不错。-RBF procedures can realize function fitting, I have personally debugging, and good results.

遗传算法的通用程序，可以根据需要改编以适应不同的应用-Generic genetic algorithm procedure can be adapted to the needs of different applications

矩形件排样优化问题是一个多目标优化问题，另一方面要考虑到生产时的下料效率-Rectangular pieces of nesting optimization problem is a multi-objective optimization problem, on the other hand, taking into account the production efficiency of the next expected

Principles of Data Mining是数据挖掘领域里面又一本经典的教材，呵呵，希望对大家有帮助-Principles of Data Mining is a data mining inside another in this classic textbook, Oh, you want to help

人工智能经典问题TSP问题的Java实现，内含源程序和调试过程生成的文件-AI classic TSP Java realize that contains source and debugging process produces files

利用Fisher分类器对数据进行分类，并画出决策面（含测试数据）-Fisher classifier using the data classification, and face painted in decision-making (including test data)

C＋＋编写的机器学习算法 Lemga is a C++ package which consists of classes for several learning models and generic algorithms for optimizing (training) the models-prepared by the machine learning algorithm Lemga C is a package which con sists of classes for several learning models an d generic algorithms for optimizing (training ) the models