时间序列预测

Gaussian小波SVM及其混沌时间序列预测

Gaussian Wavelet SVM and Its Applications to Chaotic Time Series Forecasting

基于递推合成BP网络的多变量时间序列预测模型

Multivariable Time Series Forecasting Model Based on Recurrent Composite BP Neural Networks and Its Application

多维B样条函数网络应用于非线性时间序列预测

B-spline network of multi-dimension is applied to Prediction Problem of nonlinear Time Series

基于小波消噪与BP神经网络的太阳黑子时间序列预测

Sunspot Time Series Forecast Based on Wavelet De-noised and BP Neural Networks

遗传算法改进的BP神经网络在混沌径流时间序列预测中的应用

Application of BP Networks Improved by GA in Forecasting Chaotic Runoff Time Series

基于动态学习比率BP神经网络的时间序列预测方法

Predictive Method of Nonlinear Time Series Based on Dynamic Error Correction Using BP Neural Network

基于SVM的瓦斯体积分数混沌时间序列预测

Prediction of gas concentration chaotic time series based on support vector machines

在本文中将我们改进的圆形反向传播网络模型（ImprovedCircularBackPropagation&ICBP）应用于时间序列预测，进行了单步和多步时间序列预测研究。

In this article , we applied our improved circular back-propagation ( ICBP ) network to single step and multi-steps time series prediction respectively .

基于改进Lyapunov指数的瓦斯涌出时间序列预测

Predicting on the time series of gas emission based on improved Lyapunov index

基于改进的RBF网络的混沌时间序列预测

Improved RBF Network for Chaotic Time Series Prediction

动态时间序列预测DM模型

A Forecasting Model of Dynamic Time Series

一种新型广义RBF神经网络在混沌时间序列预测中的研究

On the prediction of chaotic time series using a new generalized radial basis function neural networks

KPCASVM水文时间序列预测模型的建立与应用

Establishment and application of hydrological time series forecasting model based on KPCA_SVM

给出了其在经济时间序列预测中的应用，较为系统地阐述了RBF神经网络在经济预测中应用的步骤和过程。

The application of the RBF neural network to economical forecasting is proposed and the procedure is illustrated .

基于结构化类比的时间序列预测算法研究及其在PTA共沸精馏塔建模中的应用

Research on Structured-Analogy-Based Prediction Algorithm for Time Series and Its Application on PTA Solvent System

基于ARIMA模型的外汇汇率时间序列预测研究

Prediction of Foreign Exchange Rate Time Series Based on ARIMA Model

本文探讨用人工神经网络的反向传播（BP）算法研究铁路客运市场的时间序列预测。

This paper is concerned with using back error propagation ( BP ) of artificial network to study the market sequence prediction of railway passenger traffic .

SVR在混沌时间序列预测中的应用

The Application of SVR to Prediction of Chaotic Time Series

基于CPSO和SVM的混沌时间序列预测

Prediction of chaotic time series based on CPSO and SVM

应用Elman神经网络的混沌时间序列预测

Prediction of Chaos Time Series Using Elman Neural Networks

提供了一种基于递推合成BP网络的非线性时间序列预测方法，并针对具体实例建立多变量时间序列模型。

This paper , presents a nonlinear time series forecasting model based on recurrent composite BP networks , It also establishes a multivariable time series model is aimed at concrete examples .

文中将最小二乘支持向量机算法应用于混沌时间序列预测中，并同BP网络及RBF网络的预测结果进行了比较分析。

This paper applies Least Squares Support Vector Machine ( LS-SVM ) to chaotic time series prediction , and compares the prediction results with BP network and RBF network .

本文应用F检验定阶准则对gap时间序列预测方法进行了研究，并用模拟信号对方法的适用性进行了讨论。

In this paper F-test criterion is used in determining order of AR model to predict the gap in time series . Meanwhile we discuss the applicability of this method with modelling signal .

实例表明，基于小波消噪和LS-SVM的混沌时间序列预测模型具有较好的预测效果。

The results show that the prediction model of chaotic time series based on wavelet de-noising and LS-SVM is better .

基于SVAR的汽轮机转子振动时间序列预测

Time Series Forecast of Rotor Vibration Based on Support Vector Autoregressive

结合ICA在时间序列预测的应用，给出了基于一阶差分和最小方差误差的多分量联合重构预测排序准则。

In time series forecasting , a novel criterion has been presented based on the mechanism of first-order differential and minimum variance error under multiple components reconstruction .

在分析现有多项式非线性自适应预测法的基础上，提出了混沌时间序列预测的DCT域二次实时自适应滤波预测法；

Based on the analysis of polynomial nonlinear adaptive prediction methods existed already , a DCT domain quadratic predictor for real-time prediction of low-dimension chaotic time series is proposed .

本文重点研究基于混沌理论的自相似业务流的预测，提出了一种基于Lyapunov指数的非线性时间序列预测算法。

In this paper , we employ chaotic predictive technique to predict the self-similar traffic and put forward a new method of predicting nonlinear time series which based on Lyapunov exponent .

最后，将基于LS-SVM的时间序列预测方法应用于移动通信话务量预测领域，实现话务量的实时、在线、多步预测。

At last , we appled the above methods in mobile communication traffic prediction field and achieved real-time , online and multi-step traffic forecasting .

Box和英国统计学家GwilymM.Jenkins的名字命名的一种时间序列预测方法。

Box and British statistician Gwilym M.Jenkins .