On runoff time series forecasting, this method shows a good result, too. 3.
研究还表明，该方法在水文月径流时间序列的预测中同样有效。
Time series forecasting refers to the use of the historical observations of time series to predict the value at a future time.
本文第一章介绍了该课题的背景意义以及时间序列预测的国内外研究现状；
This paper introduces the feasibility of inner recursion networks using in non-linear ARMA model approaching and time series forecasting.
该文介绍了内回归神经网络逼近非线性ARMA模型、用于时间序列预测的可行性。
In order to improve the prediction accuracy of iron ore consumption, using a time series forecasting method based on intelligent calculation.
为了提高铁矿石消费量的预测精度，采用一种基于智能计算的时间序列预测方法。
A new methodology based on state space reconstruction and divergence calculation techniques has been developed for financial time series forecasting.
一种新的基于相空间重构和偏差计算技术的方法已被应用于金融市场预测。
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。
The fuzzy time series forecasting differ from classic time series forecasting is lead in the conception, named membership function which contribute much to figure the method.
模糊时间序列法不同于经典时间预测之处在于其引入了隶属函数的概念，在序列的预测演算中起到重要作用。
Moving average method is one of time series forecasting method, if time series have no apparent tendency moving, using moving average method can accurately reflect actual situation.
移动平均法是一种时间序列预测法，当时间序列没有明显的趋势变动时，使用移动平均就能够准确地反映实际情况。
Time series forecasting models of total food-grain consumption in China were selected by using SPSS, and were built based on the correlative relationship between quantity of consumption and time.
利用粮食消费量与时间之间的相关关系，采用SPSS程序包进行筛选，建立我国食用粮食消费总量的时序预测模型。
It discusses and compares the forecasting models using neural networks and using time series.
讨论、比较了基于神经网络和基于时间序列的预测模型。
In the final chapter, we mine stock trading data using time series method, find out the model and outliers in the data and, at last, we show the more exact forecasting model and outlier mining method.
第五章利用时间序列的方法对证券交易数据进行了挖掘，找出了数据中的模式和异常，相对传统方法而言，给出了更精确的预测模型和异常挖掘方法。
In this paper, the numerical solution of differential equation is employed to establish the forecasting model of the time series.
本文利用微分方程的数值解法对时间序列建模预测作了新的尝试。
This paper presents a method of forecasting chaotic time series.
本文提出一种混沌时间序列预测技术。
Aim To construct a new time-series forecasting model based on neural network with the capability of noise immunity.
目的建立一种新的具有抗噪声能力的神经网络时间序列预测模型。
In this paper a new method of modeling forecasting is given for the time series by using the numerical solution of differential equation.
本文利用微分方程的数值解法对时间序列建模预测作了新的尝试。
A method based on radial basis function networks for forecasting chaotic time series is proposed.
给出了基于径向基函数网络的混沌时间序列预测的方法。
These combination forecasting models are characterized with simple algorithm and comparison of forecasting effectiveness to different time series.
该模型具有计算简便的特点，而且具有可比性，能反映不同时间序列预测方法有效性。
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。
A new neural tree for modeling the time-series forecasting is proposed in the paper.
提出了一种新的神经树模型来进行时间序列预测。
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。
Because stock forecasting is a uncertain, nonlinear and nonstationary time series problem, it is difficult to achieve a satisfying prediction effect by traditional methods.
由于股票预测是不确定、非线性、非平稳的时间序列问题，传统的方法往往难以取得满意的预测效果。
There are traditional model methods of forecasting short-term load, such as time series, regression analysis, and so on.
电力系统短期负荷预测使用的方法有传统建模方法，诸如时间序列、回归分析等方法。
Hydrological time series similarity search can be used for rainfall and flood forecasting, the analysis of environment evolvement and hydrological process, etc.
水文时间序列相似性查询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。
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。
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。
An improved method for short term electric load forecasting is presented. It is based on time series methods and fuzzy logic techniques.
提出一种时间序列算法和模糊逻辑技术相结合的电力系统短期负荷预测方法。
The research on forecasting method of chaotic economic time series is the important part of the nonlinear chaotic economic dynamic systems.
混沌经济时间序列的预测方法研究是混沌经济非线性动力系统的重要内容。
In forecasting, it is unsuitable to apply Autoregressive model to time series with seasonal variation.
对于具有季节变动的时间序列，使用自回归模型进行预测是不适宜的。
In economic field, the time series models are important methods in describing and forecasting the objective economic process.
在经济领域中，运用时间序列模型来进行客观经济过程的描述和预测是一个非常重要的方法。
In economic field, the time series models are important methods in describing and forecasting the objective economic process.
在经济领域中，运用时间序列模型来进行客观经济过程的描述和预测是一个非常重要的方法。
应用推荐