蚁群算法及其在旅行商中的应用。一个非常好的论文。

手写汉字识别 应用SVM和神经网络进行识别,可自行训练-Handwritten Chinese Character Recognition Application of SVM and neural networks to identify their own training

遗传算法的一些经典程序收集-genetic algorithem2

卡内基梅隆大学，采用人工神经网络方法进行人脸训练和识别的c程序源代码，程序中注释比较详细，不多说了。-Carnegie Mellon University, artificial neural network method for training and Face Recognition c source code, procedures Notes in greater detail, not much to say.

可以自动生成qbf问题实例,但需要给定一些参数.-can produce QBF instance

运用神经网络的方法先将数据分类分析,然后再将未知类归类-The use of neural network analysis of data classification methods first, and then classify the unknown category

多目标进化算法源代码-more evolutionary algorithm source code

针对TSP问题，使用蚂蚁演算法求最佳解！程式还满美观唷！-against TSP, the use of the ant algorithm for the optimal solution! Program was one of appearance Police!

仿真1：首先把网络温度参数T固定在100，按工作规则共进行1000次状态更新,把这1000次状态转移中网络中的各个状态出现的次数Si（i＝1，2，…，16）记录下来 按下式计算各个状态出现的实际频率： Pi=Si/∑i=1,NSi=Si/M 同时按照Bo1tzmann分布计算网络各个状态出现概率的理论值： Q（Ei）=（1/Z）exp（-Ei/T） 仿真2：实施降温方案，重新计算 采用快速降温方案：T（t）= T0/（1+t） T从1000降到0.01，按工作规则更新网络状态 当T=0.01时结束降温，再让T保持在0.01进行1000次状态转移，比较两种概率-a simulation : First of all network parameters temperature T fixed at 100 and, according to the rules for a total of 1000 to update the state, this state of the 1000 network transfer of all states for the number of Si (i = 1, 2, ..., 16) all recorded determined by the formula state-of the actual frequency : Pi = Si/i = 1, NSi = Si/M in accordance with Bo1tzmann distributed computing network of states all probability the theoretical value : Q (Ei) = (1/Z) exp (- Ei/T) Simulation 2 : implementation of cooling, re-using rapid cooling programs : T (t) = T0/(1 t) T dropped to 0.01 from 1000 and, according to the rules updated network state when T = 0.01 at the end of cooling, let T at 0.01 for the 1000 state tran

一个hopfield神经网络很好的程序，与大家分享！-Hopfield neural network a very good program to share with you!

人工智能中的遗传算法权威书籍 适合初学者-Genetic Algorithms in Artificial Intelligence the authority of books suitable for beginners