一个bp神经元网络的c++实现，优化了算法，有可执行界面

遗传算法 遗传算法简称GA(Genetic Algorithm)，在本质上是一种不依赖具体问题的直接搜索方法。遗传算法在模式识别、神经网络、图像处理、机器学习、工业优化控制、自适应控制、生物科学、社会科学等方面都得到应用。在人工智能研究中，现在人们认为“遗传算法、自适应系统、细胞自动机、混沌理论与人工智能一样，都是对今后十年的计算技术有重大影响的关键技术”。-Referred to as genetic algorithm genetic algorithm GA (Genetic Algorithm), in essence is a kind of do not rely on specific issues of direct search method. Genetic algorithm in pattern recognition, neural networks, image processing, machine learning, optimization of industrial control, adaptive control, biological sciences, social sciences and so on have been applied. Research in artificial intelligence, now that the " genetic algorithms, adaptive systems, cellular automata, chaos theory and artificial intelligence, are the next ten years of the computing technology have a major impact on the key technology."

这个软件可以对输入的象素矩阵进行识别。是根据《Neural Network Design》（Martin T. Hagan等）中的关于有监督的Heb学习编写的。使用JBuilder开发的界面，使用JCreator开发的核心。-the software can input pixel matrix identification. Based on "Neural Network Design" (Martin T. Hagan, etc.) on the supervision of a study prepared by the Heb. Using JBuilder development of the interface, use JCreator development of the core.

人工智能GA问题的C语言实现，已经调试通过，含源程序和实验报告-the C language, debugging, and experiment with the source report

BP神经网络的C语言实现，对理解神经网络很有帮助。-BP neural network to achieve the C language, very helpful in understanding the neural network.

多段图的分析算法,找到最优路径,用VC编的-more of the map analysis algorithms to find the optimal path, the series with VC

遗传算法应用-Application of genetic algorithms

基于机器学习的自动逻辑推理机。本程序用归结反演策略实现了命题逻辑系统的自动推理。把要解决的问题作为一个要证明的命题，其目标公式被否定并化成子句形，然后添加到命题公式集中去,把消解反演系统应用于联合集，并推导出一个空子句(NIL)，产生一个矛盾。-based on the automatic machine learning logical reasoning machine. The procedures used attributed inversion strategy to achieve the propositional logic of automatic reasoning. Put the problem to be solved as a proposition to prove, with the goal being negated formula and shape into a phrase and then added to the Proposition formula to concentrate, digestion system for joint inversion sets and derived an empty phrase (NIL), resulting in a contradiction.

遗传算法实用程序5（pascal)-GA Utility 5 (pascal)

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,

详细介绍了MATLAB遗传算法工具箱及在工程方面的应用，有了这本书，可以很方便地使用遗传算法解决问题了-Detailed MATLAB genetic algorithm toolbox and its application in engineering, with this book, it is easy to use genetic algorithms to solve the problem of