neural network in C language

微分进化算法DE（Differential Evolution）由Storn和Price等学者于1995年首先提出。它是一种基于种群优化的新智能优化方法，它已被证明在求解过程中具有高效性、收敛性、鲁棒性等优点-Differential evolution algorithm DE (Differential Evolution) by Storn and Price and other scholars in 1995, the first place. It is a species based on the optimization of the new intelligent optimization method, which has been proved in the solving process with high efficiency, convergence, robustness, etc.

人工智能课程中关于产生式系统部分上机实验的源代码，有很大参考价值。-No

遗传优化神经网络结构，C++源代码-Genetic optimization of neural network architecture, C++ Source code

一个求解TSP问题的例子,用delphi编写.有很好的参考价值 -a TSP example, prepared with delphi. A very good reference value

Pascal Programs Printed in GENETIC ALGORITHMS IN SEARCH, OPTIMIZATION, AND MACHINE LEARNING by David E. Goldberg -Pascal Programs Printed in GENETIC ALGORITHMS IN SEARCH, OPTIMIZATION, AND MACHINE LEARNING by David E. Goldberg

一种智能语言，适合用来做专家系统 an artificial intelligence language named clips, it is useful in ES engineer-An intelligent language, suitable for expert system used an artificial intelligence language named clips, it is useful in ES engineer

neural network limulated in C

属性约简程序： 1将roughset数据库附加到SQLServer2000数据库中 2 在system.ini中设置SQLServer2000服务器ip,若在本地，则不必设置 3 在CTR表中输入决策表 4 启动roughset_getreduce.exe求约简和规则.-attribute reduction procedures : roughset database will be an additional database to SQLServer2000 2 syste m.ini set SQLServer2000 server ip, if the local, they do not need to set up three tables in the importation of CTR Decision Tables 4 start roughset_getreduce.e xe demand reduction and rules.

K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.

用局部最优探索算法求解tsp问题。。。matlab编写。附有城市坐标用于检验。 -Using local optimization algorithm to explore the issue tsp. . . matlab prepared. Coordinate with the city for inspection.