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XCSR_DE1.0
- - XCS for Dynamic Environments + Continuous versions of XCS + Test problem: real multiplexer + Experiments: XCS is explored in dynamic environments with different magnitudes of change to the underlying concepts. +Reference papers: H.H.
TravelingSalesmanProblemwithGeneticAlgorithm
- this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once) Notes: 1. Input error checki
Perceptron-and-ADALINE-network
- 这些程序包括以下方面1.使用感知器和ADALINE网络对字母进行识别。2.随机选取初始权向量，选取适当的迭代步长(对ADALINE网络)，用给出的四个输入训练样本，对上述两个网络分别进行训练，直到网络收敛；3.对Adaline网络选取不同的值，分别画出误差曲线，观察它们的变化规律；4.对感知器选取不同的初始权向量，分别计算每类训练样本到超平面的距离，观察它们的异同；5.训练结束后，检验网络的识别能力(使用100个检测样本，对应于每个取25个含噪的变形)：6.比较Adaline和单神经元感知器的分
Fuzzy_Fast_Implementation
- 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.
libsvm-2.9-string
- 某些应用的数据实例是字符串的形式.SVM使用字符串核训练模型.以下是实验代码,允许字符串输入,实现了一个字符串核.详细见帮助文档.-For some applications, data instances are strings. SVM trains a model using some string kernels. This experimental code (download zip file here) allows string inputs and implements one
fuzzy_CRUOSE_CONTROL
- 利用模糊控制做巡航速度控制利用e, dot_e，當作兩個輸入，取交集在對輸出值u做砍頭的動作，再用重心法求解，再用Runge-Kutta做疊代更改增益值將會得到不一樣的結果。-Using fuzzy control to do cruise speed control using e, dot_e, as the two inputs, the output value of taking the intersection of the decapitation of the movement
fuzzy_control_inverted_pendulum
- 利用fuzzy做倒單擺!!利用e, dot_e，當作兩個輸入，取交集在對輸出值u做砍頭的動作，現做出控制器看輸出有無正確，再用重心法求解，再用Runge-Kutta做疊代更改增益值將會得到不一樣的結果。-Inverted pendulum using fuzzy do!! Use of e, dot_e, as the two inputs, the output value of taking the intersection of the decapitation of the moveme
Takagi-Sugeno-fuzzymodel
- The fuzzy inference process discussed so far is Mamdani s fuzzy inference method, the most common methodology. This section discusses the so-called Sugeno, or Takagi-Sugeno-Kang, method of fuzzy inference. Introduced in 1985, it is similar to the Mam
AIAB
- Genetic algorithm assignment with two floating inputs works like a xor gate. show the best genome in the population. use three different methods.
bp--shenjingwangluo
- BP 神经网络用于预测 使用平台 - Matlab7.0数据为1986年到2000年的交通量 ，网络为3输入，1输出 15组数据，其中9组为正常训练数据，3组为变量数据，3组为测试数据-BP neural network to predict the use of platforms- Matlab7.0 data for 1986 to 2000, traffic volume, network, 3 inputs, 1 output 15 sets of data, of which
adaptofnnet
- 使神经网络更好地适应，从而改进其适应性，得到更好的解-ADAPTOFNNET Allow a neural network to adapt. The cell array format is easiest to describe. It is most convenient to be used for networks with multiple inputs and outputs, and allows sequences of inputs to be
Antilock-brake-system
- As it is mentioned the control of a robot arm using AFC can be considerably improved if a method is found to provide good estimates of the inertia matrix of the arm. Therefore, AFCAFL scheme which exploits the use of fuzzy logic as the inertial
Backpropagation-Neural-Network-v1.0
- This "classic" style of neural network is used for spontaneously generating an algorithm for the analysis of numeric patterns. The goal is to "teach" the network how to analyze a desired set of numeric inputs. For instance, the network might be taugh
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- 采用时序分析和BP神经网络,建立了基于时序-神经网络的车辆变速器齿轮故障诊断系统。通过 对车辆变速器齿轮运行状态特征信号进行时序分析和特征向量提取,并以此作为BP神经网络的输入向量进行网 络训练,从而实现变速器齿轮运行状态的识别与故障诊断。该系统应用于LC5T81变速器齿轮的故障诊断中,能 够比较准确地识别与诊断出变速器齿轮的跑合运行状态、磨损运行状态和故障运行状态。验证表明该诊断系统有 效、可行。 -Fault Diagnosis of Vehicle Transmissi
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- 采用时序分析和BP神经网络,建立了基于时序-神经网络的车辆变速器齿轮故障诊断系统。通过对车辆变速器齿轮运行状态特征信号进行时序分析和特征向量提取,并以此作为BP神经网络的输入向量进行网络训练,从而实现变速器齿轮运行状态的识别与故障诊断。该系统应用于LC5T81变速器齿轮的故障诊断中,能够比较准确地识别与诊断出变速器齿轮的跑合运行状态、磨损运行状态和故障运行状态。验证表明该诊断系统有效、可行。 -Fault Diagnosis of Vehicle Transmission Gear Base
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- 采用时序分析和BP神经网络,建立了基于时序-神经网络的车辆变速器齿轮故障诊断系统。通过对车辆变速器齿轮运行状态特征信号进行时序分析和特征向量提取,并以此作为BP神经网络的输入向量进行网 络训练,从而实现变速器齿轮运行状态的识别与故障诊断。该系统应用于LC5T81变速器齿轮的故障诊断中,能 够比较准确地识别与诊断出变速器齿轮的跑合运行状态、磨损运行状态和故障运行状态。验证表明该诊断系统有 效、可行。 -Based on time series analysis and BP neu
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- 采用时序分析和BP神经网络,建立了基于时序-神经网络的车辆变速器齿轮故障诊断系统。通过对车辆变速器齿轮运行状态特征信号进行时序分析和特征向量提取,并以此作为BP神经网络的输入向量进行网 络训练,从而实现变速器齿轮运行状态的识别与故障诊断。该系统应用于LC5T81变速器齿轮的故障诊断中,能 够比较准确地识别与诊断出变速器齿轮的跑合运行状态、磨损运行状态和故障运行状态。验证表明该诊断系统有 效、可行。 -Based on time series analysis and BP neu
Analyzing-Vector-Control-of-a-Grid-Connected-DFIG
- Analyzing Vector Control of a Grid-Connected DFIG under Simultaneous Changes of Two Inputs of Control System
perceptron
- matlab 实现 一个简单的神经元感知机，2个输入，1个输出-A simpled perceptron of neuron is realized by matlab,which consist of two inputs and one output
HMMtoolbox
- 此工具箱支持推理和学习HMM模型,拥有的算法有离散输出（DHMM），高斯输出（GHMM），或其混合物的高斯输出（mhmm）。-Hidden Markov Model (HMM) Toolbox for Matlab，This toolbox supports inference and learning for HMMs with discrete outputs (dhmm s), Gaussian outputs (ghmm s), or mixtures of Gaussians outp