一个很好的bp神经网络预测程序实例，有较好的预测精确性

vb写的改进的遗传算法程序。是一些通用代码，与具体问题对应的代码空出来，用的时候填进去。根据我的经验，要想用好遗传算法，代码必须自己写，因为问题不同，编码，杂交，变异算子可能都不一样。特别是杂交算子，需要根据问题调整，甚至创造出新的杂交方法。而且适应度计算的代码也需要自己写，特别是带约束的优化问题 -vb write improvement in the genetic algorithm. Some common code, with the specific issues the corresponding code space, and the time spent filling into account. According to my experience, in order to make good use of genetic algorithms, code must write their own, because different issues, coding, hybridization and mutation operator may not like. In particular hybrid operator, the need to adjust the problem, or even create a new hybrid method. But fitness calculation of the code required to write their own, especially with the constrained optimization problem

BP神经网络的设计前向型神经网络的实例，基于Matlab环境。-BP neural network design to the examples of neural network, based on the Matlab environment.

利用遗传算法搜索函数最优解的c++源程序 -use of genetic algorithm search function to the optimum solution c source

用禁忌搜索解决TSP问题，程序中使用对路径长度禁忌的方法，运行效率比较高。-Tabu search solution TSP, procedures for the use of the taboo path length, operating more efficient.

调用过程 CM = Confusion_matrix(train_predicts, train_targets) [combining_predicts, errorrate] = combining_NB(DP, test_targets, CM) DP，三维数组，(i,j,k)为第k个样本的DP矩阵 targets 为 0 1 2 -process called CM = Confusion_matrix (train_predicts, train_targets) [combining_predicts, errorrate] = combining_NB (DP, test_targets, CM) DP, three-dimensional array (i, j, k) for the k samples of DP matrix targets for 0 1 2

一套从入门到精通的Matlab学习教材，附有大量例子，包括神经网络源代码-a proficient from entry to the study and teaching of Matlab, with a large number of examples, including source code neural network

找出输入txt文件中出现的不同词汇，统计各词数目并按数目排序。使用hash表提高新词插入词表速度。-Txt file to find enter appear in a different vocabulary, the number of statistics in accordance with the number of words to sort. Use hash table to insert new words to improve the speed of the word table.

k中心点 编制和调试一个程序，它将用户输入的正规式转换为以状态图和矩阵形式表示的确定有穷自动机。 1．把正规式转换为NFA 2．将NFA确定化为DFA • ＃作为正规式的终止符 • 考虑复合正规式 • 开始状态号为0 -focal point for the preparation of k and debug a program, it will the user to enter the formal conversion to a state diagram and matrix forms express the determination of DFA. 1. The formal type is converted to NFA2. Will determine the NFA into a DFA

％ RBF 神经网络用于模式分类 ％ 使用平台 - Matlab6.5- RBF neural network for pattern classification use of the platform- Matlab6.5

人工智能课程的实验中用C语言环境实现子句归结的算法和反映-experimental artificial intelligence courses using C language environment to achieve phrase attributed to the algorithm and reflect