搜索资源列表
FUZZYPIDBP
- 模糊控制、最优控制、以及神经网络控制的集合算法比较,主要适用于初学者-Fuzzy control, optimal control, a collection of algorithms and neural network control comparison, mainly for beginners
intelligentcontrol
- 智能控制经典算法打包合集,模糊pid,神经网络pid,遗传算法pid,迭代学习控制,控制专业必备-Classic Collection packaged intelligent control algorithms, fuzzy pid, neural network pid, genetic algorithm pid, iterative learning control, not to be missed! ! ! Control professional must! ! !
FCM
- 结合模糊聚类和广义神经网络回归的聚类算法对数据进行分类-Combined with fuzzy clustering and generalized regression neural network clustering algorithm for data classification
ISODATA
- 模糊聚类虽然能够对数据聚类挖掘,但是由于网络入侵特征数据维数较多,不同入侵类别间的数据差别较小,不少入侵模式不能被准确分类。本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类.rar-Although capable of clustering data clustering mining, but due to network intrusion feature data dimension of more and different types of data betwee
9656565
- 一种新的基于遗传算法的模糊C-均值聚类的RBF神经网络-A New RBF Neural Network with GA-based Fuzzy C-Means Clustering Algorithm for SINS Fault Diagnosis
57843
- 识获取的模糊控制系统的基础上改进的遗传算法和神经网络 -Knowledge Acquisition of Fuzzy Control System Based on Improved Genetic Algorithm and Neural Networks
87532
- 基于RBF神经网络的模糊隶属度函数的参数学习算法 -Learning Algorithm of Parameters about Fuzzy Membership Functions Based on the RBF Neural Network
MATLAB-NN
- MATLAB神经网络的各类程序,包含遗传算法,神经网络,神经模糊,SVM等程序,十分实用。-All kinds of MATLAB neural network program, including genetic algorithms, neural networks, neuro-fuzzy, SVM and other procedures, very useful.
Intelligent-control
- 资料包含三个部分: 1:多智能体系统一致性迭代学习控制的理论和算法 2:运用Hopfield神经网络求解优化问题 3:模糊系统设计的原理和算法-Theory and algorithms of multi-agent system consistency Iterative Learning Control 2:: Data consists of three parts: a use of Hopfield neural networks for solving optimizat
classificiation-algorithm-overview
- 机器学习领域经典分类算法综述,包括Decision Tree(ID3、C4.5(C5.0)、CART、PUBLIC、SLIQ和SPRINT算法),三种典型贝叶斯分类器(朴素贝叶斯算法、TAN算法、贝叶斯网络分类器),k-近邻 、 基于数据库技术的分类算法( MIND算法、GAC-RDB算法),基于关联规则(CBA:Classification Based on Association Rule)的分类(Apriori算法),支持向量机分类,基于软计算的分类方法(粗糙集(rough set)、遗传
robot-control-matlab-simulation
- 一个用于机器人控制领域的matlab教程,包括自适应控制,模糊控制,神经网络控制等不同智能算法。-A field for robot control matlab tutorial, including adaptive control, fuzzy control, neural network control, such as different intelligent algorithms.
AForge.NET
- AForge.NET是一个专门为开发者和研究者基于C#框架设计的,他包括计算机视觉与人工智能,图像处理,神经网络,遗传算法,机器学习,模糊系统,机器人控制等领域。-AForge.NET is a specialized developer and researcher based C# framework designed, he included computer vision and artificial intelligence, image processing, neural netw
Intelligent-control-of-courseware
- 自能控制介绍包括模糊控制,神经网络控制,遗传算法,自持向量机,智能控制算法,PID神经网络控制-Self introduction can control including fuzzy control, neural network control, genetic algorithm, self-sustaining vector machine, intelligent control algorithm, PID neural network control
MT
- 经典智能控制算法,matlab仿真例程,有PID算法、神经网络算法、模糊算法等-Classic intelligent control algorithm, matlab simulation routines
FCGRNN
- 给予模糊均值聚类问题(FCM)的神经网络算法,对初学者进行神经网络关于聚类分析问题方面学习时一个不错的程序-Neural network algorithm for fuzzy mean clustering problem (FCM)
yichuansuanfa
- 遗传算法优化BP神经网络、改进的模糊C-均值聚类、遗传算法(粒子群算法、人工鱼群算法等)的投影寻踪模型等遗传算法的简单集合。-Genetic algorithm to optimize the BP neural network, an improved fuzzy C- average clustering and genetic algorithm,(particle swarm optimization (pso), artificial fish algorithm, etc.) of
pattern
- Matlab模式识别例程,包括神经网络算法和BP算法,C均值算法与模糊C均值算法和SVM分类算法。-Matlab pattern recognition routines, including neural network algorithm and BP algorithm, C-means algorithm and Fuzzy C-means algorithm and SVM classification algorithm.
txmssb
- 手写数字的分类聚类的不同算法识别,应用的算法有人工神经网络,模糊识别等-number recognize
RBF
- 针对传统的PID控制器参数固 定而导致在控制中效果差的问题,提出一种基于模糊RBF神经网络智能PID控制器的设计方法。该方法结合了模糊控制的推理能力强与神经网络学习能力强的特 点,将模糊控制与RBF神经网络相结合以在线调整PID控制器参数,整定出一组适合于控制对象的kp,ki,kd参数。将算法运用到电机控制系统的PID 参数寻优中,仿真结果表明基于此算法设计的PID控制器改善了电机控制系统的动态性能和稳定性。-Traditional PID controller parameters fixed
Evolutionary-ANFIS-Training
- 用MATLAB实现自适应神经模糊推理系统(ANFIS)结构训练。代码中,首先创建一个初始原ANFIS结构,然后采用遗传算法(GA)、粒子群优化(PSO)来训练ANFIS。此进化训练算法可用于解决非线性回归函数逼近问题。-Implementation of adaptive neural fuzzy inference system (ANFIS) based on MATLAB. Code, the first to create an initial original ANFIS struct