人工智能的过程表示法求解九宫问题,vc开发

SVM模式识别技术及在机械故障诊断中的应用进展-SVM pattern recognition technology and in Mechanical Fault Diagnosis of progress

人工智能动物推理系统程序-animal AI reasoning system procedures

一个关于BP网络的设计，实现一个函数的逼近，了解关于MATLAB神经网络工具箱的应用。-On the design of BP network, the realization of a function approaches, learn more about the MATLAB neural network toolbox applications.

PID仿真参考书,关于神经网络等方面的书，应用广泛。希望大家积极下载。-PID simulation of reference books, such as neural networks on the books, a wide range of applications. Hope that we actively download.

基于自组织特征映射网络的聚类分析，是在神经网络基础上发展起来的一种新的非监督聚类方法，分析了基于自 组织特征映射网络聚类的学习过程，分析了权系数自组织过程中邻域函数和学习步长的一般取值问题，给出了基于自组织 特征映射网络聚类实现的具体算法，并通过实际示例测试，证实了算法的正确性。 -Based on self-organizing feature map network cluster analysis, neural network is developed on the basis of a new non-supervised clustering method, analysis based on self-organizing feature map network clustering of the learning process, analyzed the weights of self-organization the process of neighborhood function and learning step-size problem of the general values are given based on the self-organizing feature map network clustering algorithm to achieve concrete and practical examples of tests, confirmed the correctness of the algorithm.

该程序利用遗传算法求Rosenbrock函数的极大值。该算法主要包括确定决策变量、建立优化模型、确定编码方法、确定解码方法、确定个体评价方法、设计遗传算子、确定遗传算法的运行参数等七个步骤。-the procedures for the use of genetic algorithms Rosenbrock function of great value. The algorithm including the identification of the main decision variables, the optimal model to determine coding method to determine decoding, determine individual evaluation methods, genetic operator, genetic algorithm to determine the operating parameters seven steps.

人工神经网络，利用matlab工具箱算法-Artificial neural network using matlab toolbox algorithm

SVM是一种优秀的分类算法，常用于用于回归分析和分类，而matlab语言的libSVM则为广大使用matlab进行设计的人员提供很好的帮助。-libSVM for regression classification

隐马尔科夫模型工具箱，可以广泛应用于识别等领域-HMM Toolbox, can be widely applied in areas such as identification

同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-comparison with the genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications