这个工具箱包含了重新

用C撰写遗传基因法-C genes written law

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,

神经网络相关算法，使用java语言进行描述的-Neural network-related algorithms, using the java language to describe the

FP-GROWTH算法的源代码(JAVA)-FP-Growth code and algrithem

利用matlab编写的神经网络算法，经过测试速度快效果好。-Prepared using matlab neural network algorithm, tested the effect of a good speed.

这是一个的遗传算法程序,开发平台是vc7.0-This is a genetic algorithm process, the development platform is vc7.0

遗传算法的matlab实现，举例说明遗传算法的基本实现步骤，适用于初学者-Matlab genetic algorithm to achieve, for example, shows the basic implementation steps of genetic algorithm is suitable for beginners

遗传算法的c语言实现-genetic algorithm in C Language

网络能通过学习带正确答案的实例集自动提取“合理的”求解规则，即具有自学习能力-network can learn the correct answer with examples of automatic drawing of the "reasonable" solution rules, that is self-learning ability

模糊控制相关程序，用于温度控制相关的控制实例-Fuzzy control procedures for the control of the temperature control of the relevant examples