第二、对混沌时间序列进行预测。
本文提出一种混沌时间序列预测技术。
This paper presents a method of forecasting chaotic time series.
本文的第六章讨论混沌时间序列的预测问题。
In chapter 6, we discuss the predict method of chaotic time series.
给出了基于径向基函数网络的混沌时间序列预测的方法。
A method based on radial basis function networks for forecasting chaotic time series is proposed.
机车车辆在线路上运行时的横向加速度是一混沌时间序列。
The lateral acceleration of locomotives and rolling stock running on track is a chaos time alignment.
然后将混沌时间序列的相关理论引入到风速、风功率预测中。
Then the chaotic time series theory is introduced into the wind speed prediction.
提出了一种用于混沌时间序列预测的改进型加权一阶局域法。
This paper proposes an improved adding-weight one-rank local-region method for prediction of chaotic time series.
混沌时间序列有着极为丰富和深刻的内涵，而且应用非常广泛。
Chaos time series which includes very abundant and profound meaning has widely applications.
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。
A new multi-branch time delay neural network is adopted to conduct prediction research on chaotic time series.
采用非线性混沌时间序列预报，不同于传统的时间序列分析方法。
It differs from traditional time-sequence analysis methods in which nonlinear chaotic time-sequence prediction is used.
建立了非线性降噪模型，并且应用此模型进行混沌时间序列信号检测。
A new model of nonlinear denoise is proposed and applied in the detection of chaotic time series signals.
这一结论为混沌时间序列分析方法应用于测井曲线识别领域提供了前提条件。
The obtained conclusion provides a premise for the application of chaotic time series analysis in well-log facies recognition.
结果表明，该模型能够较准确地预测交通流量时间序列和低维混沌时间序列。
Experimental results show that the proposed Volterra adaptive prediction model is capable of effectively predicting traffic flow time sequence and low-dimensional chaotic time sequence.
基于混沌时间序列的局域线性预测模型，提出了多嵌入维的短期负荷预测方法。
Based on local linear prediction model of chaotic time series, short-term load forecasting method on multi-embedding dimension is presented.
基于混沌系统局部特征，提出了一种局部动力相似的混沌时间序列的预测方法。
A method of chaotic time series prediction problem based on local dynamical similarity is proposed.
结果表明，当观测数据为非等时序列，采用灰色混沌时间序列进行分析比较有效；
The results show that when to data to be observed is unequal interval, it is more effective for the grey-chaos time series to analyse the data.
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。
Results show that wave amplitude series have chaotic characteristic and chaos time series is feasible to be applied in wave forecast study.
阐述了混沌学习算法的机理，设计了交通流量WNN混沌时间序列自适应学习算法。
Then the mechanism of the chaotic learning algorithm is described, and the adaptive learning algorithm of WNN for traffic flow time series is designed.
分析了基于记忆库混沌时间序列预测方法，引入一种改进核函数的支持向量机分类器。
Secondly the prediction technology of chaotic time series is studied based on memory-based predictor.
在深入研究混沌时间序列局域预测方法的基础上，提出了一种加权局域基函数预测方法。
The prediction method of weight local basis function is presented based on the deep research on local prediction for chaotic time series.
预测结果表明，与传统的预测方法相比，混沌时间序列预测的精度和可信度得到了提高。
Forecast result indicate that comparing with traditional forecasting method, chaotic time series method can improve the precision and reliability of forecast result.
利用混沌时间序列短期可以预测的特点，对选取的某两处煤矿构建了瓦斯浓度预测模型。
Using the ability of short-term predicting for chaotic time series, the paper constructed a gas concentration prediction model for certain coal mines.
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。
An improved GMDH-type neural network and its application to predicting chaotic time series are proposed.
基于变分贝叶斯及相空间重构理论，提出了含噪混沌时间序列相空间域线性回归预测模型。
We present a linearly regressive prediction model for noisy chaotic time series phase space based on variational Bayesian and phase space reconstructive theory.
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。
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.
本文最后以一个人工混沌时间序列为例，对该预测技术的应用效果及其影响因素给予评价和分析。
Finally, the forecasting results are evaluated, and the effect factors of the results are analysed by using of a chaotic time series created by logistic map as an example.
本文介绍了电子对抗中对混沌时间序列进行预测的一种数学模型和一种基于混沌序列的反侦察系统。
In this paper, the prediction of mathematical model for chaotic sequence in electronic antagonism and the anti-reconnaissance based on chaotic sequence are presented.
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。
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。
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.
应用推荐