关于matlab工具箱里的一些相关神经网络的程序

John Wiley & Sons,.Fuzzy Engineering Expert Systems with Neural Network Applications.[2002.ISBN0471293318]

利用遗传算法求解TSP的源代码程序 可以精确求出50城市-The use of genetic algorithm to solve TSP program source code can be precisely calculated 50 cities

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.

c 神经网络遗传算法-c neural network genetic algorithm

使用蚁群算法解决旅行商问题，mfc应用程序，城市数目及坐标在eil51.tsp里-use ant algorithm to solve the traveling salesman problem, and mfc applications, The number of cities and coordinates the eil51.tsp Lane

这是关于数据仓库与数据挖掘的Apriori算法的实现程序，基于关系型数据库的。-This is the implementation of Apriori Algorithm used in Data Warehouse and Data Mining filed, based on the Relation Database.

神经网络中学习矢量量化模型算法的源程序，属于有导师学习！-Neural network model of learning vector quantization algorithm source code, which has instructors to learn!

这是一个研究人工智能中蚂蚁算法的研究性文档,对想了解这方面内容的人相当有益,很难才找到的-This is a study artificial intelligence ant algorithm research documents, to think about it as a very useful one, it is difficult to find the

新近出现的很好的计算智能算法，具有很强的鲁棒性，用它发过论文．-It is a very good optimization arithmetic.

提出了基于最小化估计的泛化误差界非优化估计方法。目前大多数的核参数选择方法都是通过极小化了来得到最优参数值，但是求解优化问题的计算代价相当的大，并且不能很好地体现数据的分布特征。本文采用非优化技术，通过极小化泛化误差来优化核及相关参数，由于直接计算最小半径和最大间隔，避免了对优化问题的直接求解，因此可以很好地降低计算代价。并且该方法直接从样本出发，可以很好地体现数据的分布特征，不管数据分布是否均匀都可以适用。给出了基于凸包估计的SVM核选择的模型及实现算法。 -Proposed based on minimizing the estimated generalization error bound of the non-optimal estimation method. Most of the nuclear parameter selection methods are to get the best by minimizing the parameter values, but the computational cost for solving optimization problems is quite large, and can not properly reflect the distribution characteristics of the data. In this paper, the non-optimization technology, by minimizing the generalization error to optimize the nuclear and related parameters, due to the direct calculation of the minimum radius and maximum interval, avoiding the direct solution of the optimization problem, it can very well reduce the computation cost. And that the method directly from the sample one can well reflect the distribution chara