ARIMA model; Predict; Time series analysis; Hypertension; Incidence.
ARIMA模型；预测；时间序列分析；高血压；发病率。
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？
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。
The example result shows that the random-sets method is a nice approach to time series analysis.
实例结果分析表明，随机集模型是一种很好的时间序列分析方法。
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。
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。
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。
Time series analysis techniques have been successfully used in the parameter identification of structures.
时间序列分析法已成功地用于结构的参数识别。
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。
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。
Finally, We designed a pseudo experiment to talk about the linear time series analysis based on neural networks theory.
最后，设计模拟实验，探讨有关神经网络的线性时间序列预测方面的问题，得出结论。
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。
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。
The obtained conclusion provides a premise for the application of chaotic time series analysis in well-log facies recognition.
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。
First, it introduces time series analysis principle. Then, heating load and model error prediction are given by this principle.
文中首先介绍了时间序列法预报原理，接着应用该原理给出供热负荷和模型误差的预报。
The time series analysis is proposed for load forecasting of power-generating and power transmission programming in power systems.
本文提出用于电力系统发电规划和输电规划负荷预测的时间序列分析法。
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。
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。
An algorithm of feature extraction and damage alarming based on auto-regressive moving-average (ARMA) time series analysis is presented.
本文基于时间序列分析ARMA模型探讨了结构损伤特征提取和损伤预警的实现方法。
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。
Methods Using the time series analysis of cucumber downy mildew disease, to explore the forecasting method from the Angle of methodology.
方法：采用黄瓜霜霉病病情指数时间序列从方法学的角度进行预测方法研究。
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。
The methods, which combine time series analysis and neural networks, are especially studied and applied in the model-unknown nonlinear system.
特别针对模型未知的非线性系统，研究了时间序列分析和神经网络相结合的故障预报方法。
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。
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。
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。
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 case study shows that the time series analysis method is an effective and practical one for groundwater resources evaluation and system management.
实例研究表明，应用时间序列分析法模拟地下水资源系统，进行地下水资源评价和系统管理简单、易行、省时、省力。
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