资源列表
Genetic-Algorithms
- 遗传算法的运行机理及特点是具有定向制导的随机搜索技术，其定向制导的原则是：导向以高适应度模式为祖先的“家族”方向．以此结论为基础．利用随机化均匀设计的理论和方法，对遗传算法中的交叉操作进行了重新设计，给出了一个新的GA算法，称之为随机化均匀设计遗传算法．-Operating mechanism and genetic algorithm is characterized by directional guided random search techniques, the directional
some-important-algorithms-
- 这是清华徐士良出版的一些常用算法的程序代码，希望对大家有所帮助-It is published by Tsinghua XU Shi-liang code some commonly used algorithms, we hope to help
bp--shenjingwangluo
- BP 神经网络用于预测 使用平台 - Matlab7.0数据为1986年到2000年的交通量 ，网络为3输入，1输出 15组数据，其中9组为正常训练数据，3组为变量数据，3组为测试数据-BP neural network to predict the use of platforms- Matlab7.0 data for 1986 to 2000, traffic volume, network, 3 inputs, 1 output 15 sets of data, of which
Text2
- 这是一个关于用id3算法实现决策树的源代码-This is a decision tree algorithm id3 about using the source code
paper
- paper about Feature selection and parameter optimization for support vector machines: A new approach based on genetic algorithm with feature chromosomes
hamilton
- 分支定界法解旅行商问题的简单实现，用C++代码，效率经过优化后可以在1s内解规模为25左右的旅行商问题。附带了测试文件的自动生成工具。-Branch and bound method for solving the traveling salesman problem is simple to achieve, with the C++ code, the efficiency can be optimized through the solution 1s about the size of
basic
- 基本遗传算法的PPT课件，很经典。可以-PPT basic genetic algorithm courseware, very classic. Can see
matlab-ga-tool
- matlab遗传算法工具箱优化程序及实例。-matlab genetic algorithm toolbox optimization procedures and examples.
avigation
- 浮点协处理器在嵌入式组合导航计算机中的应用-Floating-point co-processor in the embedded computer of navigation
GA01knapsack
- 用VC++编程运用遗传算法及其改进模式求解01背包问题-VC++ programming with the use of genetic algorithm and its improved model for solving knapsack problem 01
chengxu
- 本文中利用遗传算法求解的问题为最短路径，该问题可描述为：在某大学校园内有多个场所，各场所之间有一个相关的距离cij ，目标就是要寻找一条从指定的起点 s 到指定的终点 t 的一条路径，使总距离最小。-This paper the problem using genetic algorithm for the shortest path, the problem can be described as: a university campus in a number of places, the
KnapsacksProblem
- 本程序将遗传算法应用于背包问题。借助了大自然的演化过程,是多线索而非单线索的全局优化方法,采用的是种群和随机搜索机制. -This procedure will be applied to knapsack problem genetic algorithm. With the evolution of nature, is more than a single clue leads the global optimization method, using population and ran