The reliability of the time-series analysis method in processing unsteady random signals is verited.
验证了时间序列分析方法在非平稳随机信号处理方面的可靠性；
During this course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction.
课程期间我们将检视数种学习技巧在一些领域上的应用如电脑视觉、电脑绘图、数据库搜索和时间数列分析与预测。
R provides still more tools for time series analysis. For example, we can plot the autocorrelation function for the living room temperature.
R还具有更多用于时间序列分析的工具。
In this paper, the theory and method of fuzzy time series analysis are presented, the model form and the parameters estimate problem are studied.
本文提出了模糊时间序列分析的理论和方法，研究了模型形式及其参数估计问题。
At present, outlier mining has attached a great importance in the field of time series analysis.
目前，在时间序列分析领域，孤立点的挖掘越来越多的受到重视。
City gas load is a multi-mode and complicated engineering system. This paper analyzes and estimates the gas load of Shenzhen by using method of time series analysis.
城市燃气负荷是一个多工况、复杂的工程系统，本文采用时间序列方法对深圳的燃气负荷进行了分析和预测。
Two kinds of models are derived; load prediction model based on building model recognition and load prediction model based on time series analysis.
提出了两种类型负荷预报模型，基于建筑模型辩识的负荷预报法和基于时间序列的负荷预报法。
Application of digital filtering and time series analysis to earthquake precursory processing is summarized in this paper.
本文概述了数字滤波和时间序列分析在地震前兆信息处理中的应用。
By time series analysis, we build models depicting the cutting tool states, coacervate information from dynamic date and construct feature vectors for discrimination.
通过时间序列分析建立反映切削状态的数学模型，从动态数据中凝聚信息，构成用于判别的特征向量。
This article discusses the main problem of time series analysis in the field of forecast application and programming.
本文讨论的主要问题是时间序列分析在预测领域的应用及编程实现。
The paper is to organically combine the time series analysis method and neural network technology in the fuzzy control technology and fractal theory to predict mine gas emission quantity.
将模糊控制技术、分形理论中的时间序列分析方法与神经网络技术有机地结合起来，并运用于矿井瓦斯涌出量的预测中。
Because these models can reflect the feature of the financial market well, they have been widely applied in the time series analysis on financial data.
由于该模型被认为是最集中反映了金融市场数据方差变化的特点而被广泛应用于金融数据时间序列分析中。
The prediction error correction is based on time series analysis, parameters estimation and optimum prediction principle.
预报误差校正是基于时间序列分析、参数估计和最优预报原理形成的。
Based on the state space analysis, the time series analysis method for identification of the stochastic continuous signals, proved as consistent convergence, is given.
基于状态空间分析，给出了连续随机信号建模的时间序列分析方法，并证明了参数估计的一致收敛性。
On the basis of traditional time series analysis and modeling methods, the thesis puts forward a new complete and simply identification method by using ar model.
本文在传统时间序列分析建模方法的基础上，提出了用AR模型的新的完整而又简单的辨识方法。
A forecast instance indicates that compared with the traditional time series analysis, the present forecast method can carry out more accurate forecast of vibration response trends.
预测实例表明，相比于传统的时间序列分析方法，这种预测方法能对振动响应的趋势进行更准确的预测。
An ARMA innovation model and the state optimal filter are designed by modern time series analysis method.
结合现代时间序列分析方法，并根据新息模型设计了状态最优滤波器。
Robinia Robinia honey is estimated by time series analysis AR (1) model, related factors?
刺槐蜂蜜日产量的时间序列分析AR(1)模型相关系数？
Furthermore, a random drift error model for IFOG is built by the method of time series analysis.
此外，采用时间序列分析方法，建立了IFOG的随机漂移误差模型。
The mid and long term forecast model based on the time series analysis has a good forecast effect.
建立在时间序列分析基础上的中长期预报模型具有很好的预报效果，可以用于作业预报。
Time series analysis is an important method of the dynamic data analysis which has extensive researches and usages in many subject fields.
时间序列分析是动态数据分析的重要方法，在多学科领域中得到广泛的研究和运用。
Adaptive signal deconvolution problem is reviewed by the new view point of the time series analysis.
本文从时间序列分析的新观点阐述自适应信号去卷问题。
The disadvantage of establishing ARMA model with traditional time series analysis is analyzed; a new model building method based on judgment rules and long autoregression is put forward.
分析了传统时间序列分析法建立ARMA模型的不足，提出了一种利用模型阶数判断准则和长自回归法建模的新方法。
The random settlement could be gotten by random prediction model that is established by smooth and stable time series analysis method.
用平稳时间序列分析方法建立随机部分模型，并预测沉降随机部分值，二者之和即为某时期沉降预测值。
As one of the branches of statistics, time series analysis focuses on the variation characters and trend of discrete ordered data series mainly.
时间序列分析是统计学的分支之一，它的研究对象是离散有序数列的变化特征和变化趋势。
The basic principle and method of time series analysis and its application in thermal error modeling on NC machine tools were presented.
提出了采用时间序列分析法进行机床热误差建模的基本原理及方法，及其在数控机床热误差补偿建模中的应用。
According to the change pattern of some parameters in metal cutting processes, this paper proposes for the first time a new time series analysis model-Autoregressive Constant model ARC (2).
本文根据切削过程中一些参数的变化规律，从理论上首次提出了一种新的时间序列分析模型，即常系数固定价ARC(2)模型。
Time series analysis and statistical test provide quantitative criteria to determine the optimum observation frequency.
时间序列分析和统计检验提供了优化地下水位监测频率的定量标准。
Test of nonlinearity of time series is very important for nonlinear time series analysis and study of chaotic dynamics.
时间序列的非线性检测对于非线性时间序列分析、混沌特性研究有着重要意义。
Test of nonlinearity of time series is very important for nonlinear time series analysis and study of chaotic dynamics.
时间序列的非线性检测对于非线性时间序列分析、混沌特性研究有着重要意义。
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