RBF neural network is applied to time series forecast with the same data in order to compare the forecast effect with LS-SVM model.
最小二乘支持向量机回归预测对训练样本数据区间内的预测精度很高，但是对前向外推预测效果不是很好；
One of the current forecast methods is time series forecast which constructs models according to the historical data before using it to forecast the future.
时间序列预测是预测领域内的一个重要研究方向，时间序列预测是一种根据历史数据构造时间序列模型，再把模型外推来预测未来的一种方法。
In the study of time series forecasting in ground states, the method for recognition and processing singular values is proposed, then LS-SVM is applied to forecast.
针对基态趋势客流预测问题，研究了进行奇异值检测处理并运用最小二乘支持向量机进行预测的解决方案。
This means is fit for the time series forecast which difficult to judge the time series typical character. It don't need cost much time to search explaining variable as regression analysis.
该方法适合于对时间序列的典型特征难以做出判断的时间序列的预测，而且它也无需像回归分析中必须花费很多时间寻找解释变量。
Combining the advantages of regression analysis methods and time series forecast model with equal step length, a compound forecasting model was set up , and was tested with engineering data.
结果显示，把最小二乘支持向量机回归预测与等步长时序预测相结合的预测方法应用于地下工程围岩位移监测数据的分析及预测是可行的；
In this paper, the Theory of Corrclation Analysis on Time Series is applied to very-short-term power system load forecast.
本文将时间序列相关分析理论应用于电力系统超短期负荷预报。
In this paper, a new model system is introduced, which synthetically applies time series model, nonlinear regression and combination forecasting model to forecast the change of the market price.
文章通过对一套市场价格预测模型体系的介绍，综合运用时间序列模型、多元非线性回归和组合模型来预测市场价格走势，探索从多角度综合预测市场价格的问题。
Because it cannot reach the two constrained conditions, previous forecast value based on time series composition data cannot add up to 1.
由于不能满足成分数据两个约束条件，以往对按时间顺序收集的成分数据预测，其预测值之和不等于1。
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。
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。
Linear growth model is widely used in the analysis and forecast of time series in economic and biological fields.
线性增长型模型被广泛应用于经济领域和对生物信号的时间序列的分析和预报。
Aiming at the abnormity of the phase and groove number, hardware redundancy and difference method is used to forecast time series and the problems are resolved.
针对定位传感器应用中相角和齿槽数信号异常的问题，利用硬件冗余和差分法进行时间序列预测，解决了该类问题。
Aim at the trait of time series, investigate the different ARIMA patterns, put forward the ARIMA model and forecast and estimate aim at special market.
针对其时间序列的特点，研究了ARIMA的不同模式，提出了面向特定市场的ARIMA模型，及其预测和估计方法。
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。
This article demonstrates that deformation forecast will be performed by a comprehensive method of non linear regression model combined with time series analysis.
本文将讨论综合运用非线性回归模型和时间序列分析的方法进行变形预报。
And some existing methods of oil demand forecast are analyzed, such as Time Series Analysis, Artificial Neural Network method, Gray System method and Consumption elasticity coefficient method.
并且分析了现有的一些石油需求预测方法，这些方法包括：时间序列法、人工神经网络方法、灰色系统法、弹性系数法等。
First this article used expands the Dick - fuller model the card index to carry on the time series analysis to our country in, finally indicated the index the returns ratio might not forecast.
首先本文采用扩展迪克—富勒模型对我国上证指数进行了时间序列分析，结果表明指数的收益率是不可预测。
After defining a effective index for process similarity, an analogue model, which is suitable for doing similarity forecast for a time series, was established.
通过寻找过程相似的有效指标，建立了一个适合于时间序列分析的相似预报模式。
Founded on change speciality of series of dam safety monitoring forecast, artificial neural networks and nonlinear models of time series based on genetic algorithms are applied.
根据大坝监测数据在时序上变化特征，应用了神经网络和基于遗传算法的时间序列的非线性预测模型。
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。
User can choose a region (grid box) to display the forecast time series by clicking over the map directly or clicking the place name on the list to select the belonging region.
用户可直接按地图或在清单上按地方名称，以选择所属区域(方格)的预测时间序列。
Conclusion: The exponential smoothing method could be employed to forecast a time series of one dimension for cucumber downy disease.
结论：可以利用指数平滑法对霜霉病一维时间序列进行预测。
The theory of linear regression and the theory of moving average are applied to analyse single data in time series, the model of a linear moving self regression forecast are given out.
应用线性回归分析和移动平均理论，对按时间次序排列的单一数据序列，给出了一种线性移动自回归预测模型，并对原始数据受不确定因素影响而产生的随机振荡，给出了合理的控制区间和运行通道。
Hydrological time series similarity search can be used to rain and floods forecast, and the analysis of environment evolvement and hydrological process, etc.
水文序列相似性查找可用于雨洪过程预测、环境演变分析、水文过程规律分析等方面。
Simultaneously, the forecast theory and method of nonlinear time series is established, which combines mechanism of the time space system with analyzing historical data.
结合时空系统机制和历史资料的分析，建立非线性时空序列预测理论与方法。
Objective The approach and procedure to fit time series with ARIMA models are discussed briefly. The application to forecast hepatitis B is given to help infectious diseases forecasting system.
目的阐述A RIMA模型拟合时间序列的方法和步骤，并将其应用于乙型肝炎的预测，为传染病预警系统提供决策依据。
The time series method is one of common methods for forecasting water consumption. The prediction accuracy on water consumption can be guaranteed by the selection of forecast models.
时间序列法是用水量预测的常用方法，其中预测模型的选择是提高预测精度的关键。
Time series method is adopted for building the strong wind monitoring and warning system of Qinghai-Tibet Railway to realize the short-term forecast of the wind speed along the line.
青藏铁路大风监测预警系统采用时间序列法实现沿线风速的短时预测。
The most important purpose to analyze time series with transfer function model is improving the precision of forecast.
使用传递函数模型对时间序列进行分析，最大的意义在于提高预测精度。
The most important purpose to analyze time series with transfer function model is improving the precision of forecast.
使用传递函数模型对时间序列进行分析，最大的意义在于提高预测精度。
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