实现了图的搜索算法，包括深度优先搜索，广度优先搜索，Dijstra算法，A*算法等较典型的搜索算法，同时可以进行图的输入和编辑等操作，仅供大家参考。...

模糊算法，实现了求交法计算模糊蕴含关系、最大最小法进行合成运算、求并法计算输出量的模糊集合、加权平均法计算实际的清晰控制量等部分的详细代码。-Fuzzy algorithm, the realization of the intersection method to calculate fuzzy implication relations, max-min method for synthesis of computing, and method for output fuzzy sets, the weighted average method to calculate the actual volume of clear control of part of the detailed code.

神经网络hopfield源码- Nerve network hopfield source code

一个牛人的神经网络支持向量机代码,对于搞模式识别的朋友强烈推荐!-A wonderful program of svm code coming from a superman,and strong recommendation to someone who learn about pattern-recognition .

greedy em 混和模型训练算法-greedy em hybrid model training algorithm

这个程序对快速实现模糊逻辑控制很有用。假设这个逻辑控制有两个输入和一个输出，用各种选择来实现它。-This procedure is the rapid realization of the usefulness of fuzzy logic control. Assuming that there are two logic control inputs and one output, with various options to achieve it.

神经网络算法原程序内容较详细。希望大家仔细讨论这个问题。-neural network algorithm original program content in more detail. We hope to discuss this issue carefully.

模糊数学与人工智能技术 -fuzzy mathematics and artificial intelligence technology

一个遗传算法的matlab实现源程序。希望对大家有所帮助。-A genetic algorithm matlab source realize. Would like to help everyone.

八数码难题源代码-eight digital source code problems

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.