This procedure using genetic algorithm optimization of PID parameters.

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.

考虑3个神经元的hopfield网络，每个神经元有一个阀值和一个权重，定义存储在网络中的目标平衡点中为矩阵T的两个三指定存储在网络中的目标平衡点 -Consider three neurons hopfield network, each neuron has a threshold and a weight, the definition is stored in the network, the goal of equilibrium point for the matrix T of the two three-designated storage in the network

NSGA-II遗传算法的文档，里面的内容比较好理解，是学习遗传算法的必备知识-Genetic Algorithm NSGA-II of the document, which is better understanding of the content is a genetic algorithm to learn the knowledge necessary

介绍支持向量机工具箱的 使用-svn guide

用于求解TSP问题的matlab源代码，需要读取距离矩阵-Used to solve TSP problem matlab source code, need to read the distance matrix

粒子群算法的vb源程序，可以自定义算法参数，实现对6个非约束性测试函数极小值的全局优化，动态显示粒子的移动。低维下，优化效果很好。直接解压，无须密码。请多指正。-PSO algorithm vb source, the algorithm can define parameters to achieve the six non-binding function tests minimum of global optimization, dynamic display particle movement. Low-dimensional, optimize the results very good. Direct decompression without passwords. Please correct.

支持向量机程序(2)Text Windows Svm-A program of Text Windows Svm based on support vector machines.

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本文在学习探讨VSM算法的同时，对SVM在液压系统故障诊断中的应用进行了论述。以液压设备中常见的克令吊为研究对象，运用支持向量机理论对其进行故障诊断的仿真研究和实验研究，其中包括实验系统数学模型的设计、仿真模型的建立(用SIMUL工NK仿真软件建立仿真模型)、特征参数的提取、数据的采集等。-In this paper, VSM learning algorithm to explore the same time, SVM in the hydraulic system fault diagnosis are discussed. With hydraulic equipment in the common crane as the research object, using support vector machine theory of their fault diagnosis simulation and experimental studies, including a mathematical model experimental system design, simulation model (using SIMUL Engineering Simulation NK Software to build simulation models), the extraction of characteristic parameters, data collection and so on.

模式识别在珠宝鉴定中的应用，该文是基于模式识别应用领域的文档类文献。-Pattern Recognition in jewelry appraisal application, the article is based on pattern recognition applications of the document class literature.