Finally, connecting embedding theory with prediction errors, we propose a new prediction method to chaotic time series based on embedding technique and prediction errors on tested sets.
最后，结合嵌入理论和预测误差，提出了基于嵌入技术和确定集上预测误差的混沌时序预测方法。
Based on this, the average predictable size and the longest predictable size of chaotic time series are provided in this paper to definite the time range of short-term prediction.
基于此，给出了混沌时间序列的平均可预测尺度及最长可预测尺度，以此来界定短期预测的时间范围。
To understand the frequency and chaotic characteristics of the particle colliding force, the time series of particle colliding force are analyzed by power spectrum analysis and chaotic theory.
通过对颗粒碰撞压力时间序列的功率谱分析和混沌分析，研究了其频域特性和混沌特征。
A new multi-branch time delay neural network is adopted to conduct prediction research on chaotic time series.
采用新型多重分支时间延迟神经网络进行混沌时间序列预测研究。
Based on the delay-coordinate reconstruction and bilinear expressions in the phase space of a chaotic system, a bilinear adaptive filter was designed to predict low-dimensional chaotic time series.
基于混沌动力系统相空间的延迟坐标重构和双线性表达式，设计了预测混沌时间序列的双线性自适应预测滤波器。
This paper discusses chaotic characteristic of the power daily load of Sichuan Province based on saturation correlation dimension, and concludes that daily load time series belong to chaotic series.
基于饱和关联维数法，对四川省全省电力系统日负荷序列的混沌特征进行定量分析，得出日负荷时间序列具有混沌性的结论。
Based on the deterministic and nonlinear characterization of the chaotic signals, a new reduced parameter nonlinear adaptive filter is proposed to make adaptive predictions of chaotic time series.
基于混沌动力系统的相空间延迟坐标重构，利用混沌序列固有的确定性和非线性，提出了用于混沌时间序列预测的一种少参数非线性自适应滤波预测模型。
In order to solve serious urban transport problems, according to the proved chaotic characteristic of traffic flow, a non linear chaotic model to analyze the time series of traffic flow is proposed.
为了解决日益严重的城市交通问题，本文根据交通流已被证明的混沌特性，尝试采用非线性混沌模型来分析交通流时间序列。
An improved GMDH-type neural network and its application to predicting 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。
The nonlinear dynamic theory and the chaotic time series analysis method were adopted to examine the nonlinear characteristics of strong earthquake ground motions in this paper.
引入非线性动力学理论和混沌时间序列分析方法考察强震地面运动加速度时程的非线性特征。
Emphasis is given on the surrogates data method, which is firstly applied to chaotic hydrological time series.
重点讨论了替代数据法的计算和应用，并首次将其应用到水文领域中。
Chaotic time series analysis provides a new approach to analyzing, examining and diagnosing dynamics system, and resolves problem according to the essence of chaos dynamics signals.
而混沌时间序列分析为动力学系统的非线性信号分析、检测及诊断提供了一条全新的途径，着眼于从混沌动力学系统的本质去解决问题。
Results show that wave amplitude series have chaotic characteristic and chaos time series is feasible to be applied in wave forecast study.
结果表明，浪高时间序列存在混沌现象，混沌时间序列法可应用于海浪预报的研究。
As a new type of recurrent neural network, echo state network (ESN) is applied to nonlinear system identification and chaotic time series prediction.
ESN(回声状态网络)是一种新型的递归神经网络，可有效处理非线性系统辨识以及混沌时间序列预测问题。
According to the nonlinear characteristics of landslide displacement time series, the nonlinear chaotic model is presented applying the forecasting method of chaotic time series.
根据滑坡位移时间序列的非线性性质，应用混纯时间序列预测方法，建立滑坡预测的非线性混纯模型。
According to the nonlinear characteristics of landslide displacement time series, the nonlinear chaotic model is presented applying the forecasting method of chaotic time series.
根据滑坡位移时间序列的非线性性质，应用混纯时间序列预测方法，建立滑坡预测的非线性混纯模型。
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