Description: 基于局域法多步预报模型的混沌时间序列预报模型，对多个典型混沌序列的仿真测试表明，本算法具有良好的多步预测精度和较好的抗噪声能力-based multi-step prediction model of chaotic time series prediction model, a number of typical chaotic sequence of simulation tests show that the algorithm has a good multi-step forecast accuracy and better noise immunity Platform: |
Size: 227328 |
Author:蔡烽 |
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Description: 混沌时间序列预测(chaotic time series prediction)中的Volterra级数一步预测 、Volterra级数多步预测方法-Prediction of chaotic time series (chaotic time series prediction) in the prediction step Volterra series, Volterra series multi-step prediction method Platform: |
Size: 12288 |
Author:李洁 |
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Description: matlab编写的基于混沌时间序列的神经网络预测，包括一步和多步预测算法。-matlab prepared chaotic time series based on the neural network to predict, including step and multi-step prediction algorithm. Platform: |
Size: 9216 |
Author:jcuaon |
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Description: :针对时滞系统的特点和采用神经网络单值预测控制存在的不足,提出了多步超前预测与补偿的控制算
法,有效地增加了控制力度,改善了动态性能,并论述了增加的预测与补偿步数与稳定的关系
-With regards to the characteristics of time-delay system and the weakness of single predictive control, this pa-
per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively,
and improves dynamic characteristics ofthe system. The paper also discusses the relationship between the step number of predic-
tion and compensation and the stability of systems
Platform: |
Size: 1024 |
Author:liubo |
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Description: 动态矩阵的预测控制源程序，可以实现预测控制中的模型预测和优化算法。- this pa-
per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively,
and improves dynamic characteristics ofthe system. The paper also discusses the relationship between the step number of predic-
tion and compensation and the stability of systems.
Platform: |
Size: 1024 |
Author:liubo |
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Description: 对混沌时间学列但不预测及多步预测的输入信号信号归一化处理-Studies of chaotic time series prediction and multi-step, but not predictable input signal signal normalized Platform: |
Size: 5120 |
Author:王孔峰 |
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Description: 预测控制是一种新型的控制算法之一。经典的PID控制方法简单方便,但是精度不高。近年来发展的自适应、自校正方法精度高,但其本质要求在线辨识对象模型,对过程的未建模动态和扰动的适应能力差,鲁棒性不好。预测控制方法集PID和自适应方法二者之长,是一种面向工业过程特点、对模型要求低、在线计算方便、控制精度高的算法。数字计算机向小型、高速、大容量、低成本方向的发展,为预测控制这类新算法的实现提供了物质基础。 本文以PCT—Ⅲ型过程控制系统装置为平台,将预测控制算法运用到实际系统中去,该装置分为水位系统和温度系统。本文是将多步预测控制算法运用到温度系统。应用控制软件采用北京亚控公司的组态王软件(KingView),它界面设计能力强,也可以简单编程,但计算能力差,不能进行矩阵计算。而在温度多步预测控制中,计算量大,编程复杂,因此引入Matlab软件解决计算和编程,要解决的问题是MATLAB和组态王的数据交换,采用动态数据交换技术(DDE)。 预测控制算法有多种,本文采用的是动态矩阵控制方法(DMC)。-Predictive control is one of a new control algorithm. The classic PID control method is simple, but the accuracy is not high. In recent years the development of adaptive, self-calibration method is accurate, but its object model online identification of the essential requirements of the process unmodeled dynamics and disturbances poor adaptability, robustness is not good. Prediction and adaptive PID control method sets the length of the two methods is a feature for industrial processes, low requirement on the model, online convenience of calculation, the control algorithm for high accuracy. Digital computers to small, high-speed, large capacity, lower costs of development, such as predictive control implementation of the new algorithm provides the material base. In this paper, PCT-Ⅲ type of process control system devices as a platform, the predictive control algorithm to apply to the actual system, the device is divided into water system and temperature system. This is a multi-step pre Platform: |
Size: 3517440 |
Author:王明 |
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Description: 混沌时序多步预测函数 chen函数的matlab仿真，非常有用，连续的非线性函数-Multi-step prediction of chaotic time series function chen function matlab simulation, very useful, continuous nonlinear function Platform: |
Size: 219136 |
Author:王聪 |
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Description: 混沌时序多步预测函数，采用matlab编程，简单易懂-Chaotic time series multi-step prediction function, using the Matlab programming, easy to understand Platform: |
Size: 219136 |
Author:王建华 |
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Description: 针对神经网络的瓦斯预测模型存在的泛化性能差且存在易陷入局部最优的缺点，提出了
基于最小二乘支持向量机(LS-SVM)时间序列瓦斯预测方法．由于标准最小二乘支持向量机
(L孓SVM)要求样本误差分布服从高斯分布，且标准LS-SVM丧失鲁棒性与稀疏性等特点，提出
了基于加权LS-SVM的瓦斯时间序列预测的方法，从而提高了标准L孓SVM模型的鲁棒性．其
中时间序列的嵌入维数与延迟时间采用了微熵率最小原则进行选取，在此基础上给出了基于加
权L孓SVM实现多步时间序列预测的算法实现步骤．最后利用MATLAB 7．1对其进行仿真研
究，通过鹤壁十矿1个突出工作面的瓦斯涌出数据实例对模型进行了验证．结果表明，加权
SVM模型比标准的L§SVM明显提高了鲁棒性，可较好地实现时间序列数据的多步预测．-The neural network gas prediction model is poor in generalization performance and
easy in fafling into the local optimal value．In order to overcome these shortcomings，we pro—
pose the time series gas prediction method of least squares support vector machine(L§SVM)．
However，in the LS-SVM case，the sparseness and robustness may lose，and the estimation of
the support values iS optimal only in the case of a Gaussian distribution of the error variables．
So，this paper proposes the weighted L孓SVM tO overcome these tWO drawbacks．Meanwhile，
the optimal embedding dimension and delay time of time series are obtained by the smallest dif—
ferential entropy method．On this basis，multi-step time series prediction algorithm steps are
given based on the weighted LS-SVM．Finally，the data of gas outburst in working face of Hebi
lOth mine iS adopted to validate this model．The results show that the predict effect of shortterm
the face gas emission is better using the weighted LS-SVM model than using Platform: |
Size: 490496 |
Author:wanggen |
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Description: 混沌时间序列的RBF一步及多步预测，工具matlab，Chaotic time series RBF one-step and multi-step prediction-混沌时间序列的RBF一步及多步预测
Chaotic time series RBF one-step and multi-step prediction Platform: |
Size: 10240 |
Author:菜头 |
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Description: 多分类学习及神经网络，机器学习相关，基于matlab计算-ex3.m- Octave script that will help step you through part 1
ex3 nn.m- Octave script that will help step you through part 2
ex3data1.mat- Training set of hand-written digits
ex3weights.mat- Initial weights for the neural network exercise
submitWeb.m- Alternative submission script
submit.m- Submission script that sends your solutions to our servers
displayData.m- Function to help visualize the dataset
fmincg.m- Function minimization routine (similar to fminunc)
sigmoid.m- Sigmoid function
[?] lrCostFunction.m- Logistic regression cost function
[?] oneVsAll.m- Train a one-vs-all multi-class classi er
[?] predictOneVsAll.m- Predict using a one-vs-all multi-class classi er
[?] predict.m- Neural network prediction function Platform: |
Size: 7608320 |
Author:张伟强 |
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Search - matlab multi step prediction