多变量混沌时间序列预测,chaotic time-series prediction
1)chaotic time-series prediction多变量混沌时间序列预测
1.Considering the shortages in the prediction of chaotic time-series using single variable,this paper studies a new multivariatechaotic time-series prediction model,which is based on the principal components analysis(PCA) and echo state networks(ESN).针对多变量预测过程中的维数过高问题,文章结合主元分析理论(PCA)和回声状态网络(ESN),构建了基于PCA和ESN的多变量混沌时间序列预测模型,将PCA降维后的时间序列数据输入ESN网络进行预测分析。
英文短句/例句
1.Predication of multivariable chaotic time series based on maximal Lyapunov exponent基于最大Lyapunov指数的多变量混沌时间序列预测
2.Prediction to Multivariate Chaotic Time Series and Its Application to Stock Market;多变量混沌时间序列预测及其在股票市场中的应用
3.Study on Predicting Multivariate Chaotic Time Series by Principle Component Analysis;基于主成分分析的多变量混沌时间序列预测研究
4.Volterra adaptive real-time prediction of multivariate chaotic time series多变量混沌时间序列Volterra自适应实时预测
5.Research on Variable Selection and Prediction Algorithm for Multivariate Chaotic Time Series;多元混沌时间序列的变量选择及预测方法研究
6.Weighted Prediction of Multi-Parameter Chaotic Time Series Using Least Squares Support Vector Regression(LS-SVR)基于新息的多参量混沌时间序列LS-SVR加权预测
7.Chaotic time series prediction based on the variational Bayesian kriging model变分贝叶斯Kriging模型预测混沌时间序列
8.Support Vector Machines for the Chaotic Time Series Prediction基于支持向量机的混沌时间序列预测
9.The Whole-region Method of Chaotic Time Series for Slope Deformation Prediction边坡变形预测的混沌时间序列全局近似方法
10.Chaotic time series prediction based on ANFIS with adaptive mutation differential evolution algorithm混沌时间序列的自适应变异差分进化ANFIS预测
11.Temperature Prediction for Substations Based on Chaotic Time Series基于混沌时间序列的变电站设备温度预测
12.Chaotic Analysis and Prediction for Traffic Flow Time Series;交通流量时间序列混沌特性分析及预测研究
13.Research on Analysis of Correlation and Prediction Modeling for Multivariate Chaotic Time Series;多元混沌时间序列相关性分析及预测方法研究
14.Multiple clusters echo state network for chaotic time series prediction用于混沌时间序列预测的多簇回响状态网络
15.Study on Distributional Chaos Theory and Prediction Technology of Chaotic Time Series;分布混沌理论与混沌时间序列预测方法研究
16.Prediction of chaotic time series based on CPSO and SVM基于CPSO和SVM的混沌时间序列预测
17.Gaussian Wavelet SVM and Its Applications to Chaotic Time Series ForecastingGaussian小波SVM及其混沌时间序列预测
18.Chaotic time series prediction based on fuzzy tree基于模糊树模型的混沌时间序列预测
相关短句/例句
multivariate chaotic time series多变量混沌时间序列
1.Volterra adaptive real-time prediction ofmultivariate chaotic time series多变量混沌时间序列Volterra自适应实时预测
2.The methods to determine time delays and embedding dimensions in the phase space delay reconstruction ofmultivariate chaotic time series are proposed.提出了多变量混沌时间序列相空间延迟重构中延迟时间间隔和嵌入维数的选取方法 ,给出了多变量混沌时间序列的局部平均预测法 ,局部线性预测法和BP神经网络预测法等 3种非线性预测方法 。
3)chaotic time series prediction混沌时间序列预测
1.Reservoir neural state reconstruction andchaotic time series prediction;储备池状态空间重构与混沌时间序列预测
2.Multiple clusters echo state network forchaotic time series prediction用于混沌时间序列预测的多簇回响状态网络
4)predicting chaotic time series混沌时间序列预测
1.An improved GMDH-type neural network and its application topredicting chaotic time series are proposed.这种用改进了的自组织方法所构成的GMDH型神经网络可以应用于混沌时间序列预测。
5)Multivariate Time Series Prediction多变量时间序列预测
6)uni-variant time series forecasting单变量时间序列预测
1.The coefficient sequences decomposed by this novel method possessed time-invariant capability and eliminated the data distortion phenomenon around right boundary, which made it feasible that the traditional forecasting models such as Neural Networks combining with wavelet transforms could apply to theuni-variant time series forecasting task.使用该算法得到的系数序列,在具备时移不变性的同时,消除了右侧边界存在数据畸变的现象,使小波分析技术结合神经网络等传统预测模型的方法应用于单变量时间序列预测任务具备可行性。
延伸阅读
离散时间周期序列的离散傅里叶级数表示 (1)式中χ((n))N为一离散时间周期序列，其周期为N点，即式中r为任意整数。X((k))N为频域周期序列，其周期亦为N点，即X(k)=X(k+lN)，式中l为任意整数。从式(1)可导出已知X((k))N求χ((n))N的关系(2)式(1)和式(2)称为离散傅里叶级数对。当离散时间周期序列整体向左移位m时,移位后的序列为χ((n+m))N，如果χ((n))N的离散傅里叶级数(DFS)表示为,则χ((n+m))N的DFS表示为
