BP神经网络实现回归程序，神经网络可以从reunificat学习…

有关bp神经网络预测的-bp of the neural network forecast

用GAlib库实现的解决0/1背包问题的遗传算法程序源代码。- Solution 0/1 knapsack question heredity algorithm procedure source code realizes which with the GAlib storehouse.

遗传算法的实现,c++/vc++/遗传算法的学习安例!-genetic algorithm to achieve, c/vc/GA-cases of learning!

遗传算法的Matlab程序，用于数值优化-GA Matlab procedures for Numerical Optimization

决策树算法 经典的ID3算法 用于决策树规则学习等等 在规则学习以及分类中有重要的作用-classic decision tree mode for classification and rule learning

C4.5决策树matlab程序,本人找了很久才找到，绝对能用-C4.5 Decision Tree code

详细介绍了人工智能在故障诊断中的应用 有实例-Details of the artificial intelligence in fault diagnosis are examples of

微分进化算法的Labview版本，内为一个无约束连续变量的全局优化问题-Differential evolution algorithm Labview version, for a continuous variable unconstrained global optimization problem

C++,Fortran和Matlab分别实现的bp算法程序 方便初学者学习和调用-C++, Fortran and Matlab algorithm bp, respectively, procedures realize the convenience of beginners to learn and call

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