基于Matlab的函数优化遗传算法程序 .

神经网络学习二维非线性函数 ,多维非线性辨识的MATLAB程序-neural network learning 2D nonlinear function, multi-dimensional nonlinear identification procedures MATLAB

混合生源 加工-Mixed biogenic processing

BP算法与人工只能的结合。-BP algorithm and the only artificial light.

利用遗传算法优化BP神经网络 即用遗传算法代替BP网络中的训练函数-The use of genetic algorithm to optimize BP neural network using genetic algorithms in place of BP network training function

遗传算法优化神经网络结构源程序-Genetic algorithm neural network structure source

神经网络C程序的第9章-neural network C procedures for the Chapter 9

模糊神经网络采用matlab编程 o install NEFCON follow these steps: 1. Unpack the tar file NEFCON.TAR into your MATLAB working directory: tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STARTUP M-file to initialize NEFCON.-FNN using Matlab programming o install NEFCON follow these steps : 1. Unpack the tar file NEFCON.TAR MATLAB into your working directory : tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STARTUP M-file to initialize NEFCON.

遗传算法，包含选择，交叉，变异等操作，可求出Y=sin(x)在0-2π的最大值和最小值-Genetic algorithm, including selection, crossover and mutation operation, etc., can be obtained Y = sin (x) at the 0-2π Maximum and minimum

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.

MCRGSA------组播路由问题遗传模拟退火算法 ％M-----------遗传算法进化代数 ％N-----------种群规模，取偶数 ％Pm----------变异概率调节参数 ％K-----------同一温度下状态跳转次数 ％t0----------初始温度 ％alpha-------降温系数 ％beta--------浓度均衡系数 ％ROUTES------备选路径集 ％Num---------到各节点的备选路径数目 ％Cost--------费用邻接矩阵 ％Source------源节点标号 ％End---------目的节点标号组成的向量 ％MBR---------各代最优路径编码-MCRGSA------ Multicast Routing genetic simulated annealing% M----------- genetic algorithm algebra% N----------- population size, even take Pm----------% probability parameter variation%----------- same temperature K Jump under a number of state----------% t0 initial temperature cooling% alpha------- beta coefficient%-------- balanced concentration coefficient% ROUTES------ Alternative Path Set% Enable--------- nodes to the number of alternative paths%-------- Cost adjacent costs Matrix% Source------ source node labeling% End--------- destination node labeling Group Vector%% of the MBR--------- generations optimal path coding