针对二次指数平滑模型的新构思对其它指数平滑模型同样适用。
This new conception is also suitable for other exponential smoothing models.
通过赋予合理权重，将C-D生产函数模型、多元回归模型和指数平滑模型加权组合。
The model which combined Cobb-Douglas production function, multiple regression model and exponential smoothing model can improve the accuracy of fix and forecast by proper weighs.
通过分析行程时间时间序列的时变特性，利用指数平滑模型进行预测，最后提出合理的修正方法。
Then, we make prediction with moving exponential average model after the analysis of the travel time series. Finally, we present reasonable justification.
一次指数平滑模型充分体现了负荷连续变化的趋势性和周期性，但是没有详细考虑天气因素对负荷的影响。
Single exponent smoothness model fully embodies the characters of trend and cycle of the continuous varying power load, but it can not think about the effect of the weather elements carefully.
并且对基于神经网络的组合预测方法进行了研究，提出了一个神经网络和指数平滑模型组合运用的预测算法。
After study of the combined forecasting methods based on the ANN theory, it is put foreword that Exponential-Smooth (ES) and ANN combine a new prediction algorithm.
又以预测误差平方和SSE最小为目标，构造了优选并自动生成最佳平滑参数使平滑模型得以优化的最速下降算法，增强了指数平滑模型对时间序列的适应能力。
Aiming the square sum of error (SSE), we construct the algorithm to iterate and select an optimal parameter for optimizing the new models, which ADAPTS the model to time series more.
(in Chinese)王昕，程小雯，房师松，等。指数平滑模型在流感样病例预测中的应用[J]。中国热带医学，2011,11 (8)：938—939。
Wang x, Cheng XW, Fang SS, et al. Application of exponential smoothing model in forecasting influenza incidence [J]. China Tropical Medicine, 2011, 11 (8) : 938-939.
具体如回归预测法、指数平滑法、灰色模型预测法、BP神经网络法、RBF神经网络法。
Such as the return of specific prediction method, smoothing index, grey model prediction, BP neural network, RBF neural network .
研究了有关布朗单一参数指数平滑经济预测模型的系数的估计问题，整理并给出了比较完整的证明。
This paper analysized the estimation problem on coefficient of Brown single parameter index smooth economic prediction model followed by giving a complete attestation.
还建立了基于最小二乘法曲线拟合与指数平滑法的需求量预测模型。
Additionally, a model of demand forecast, which bases on methods of least square and exponential smoothing, also be made.
回归分析法、灰色系统模型法和指数平滑法是目前常用的水上交通事故预测方法。
Regression analysis, grey-system and exponential smoothing method are in common use as forecasting methods of maritime accidents nowadays.
对指数加权平滑模型进行了改进，使之能适用于多种不同变化规律的参数的预报。
The exponent weighted gliding average model is improved to fit in with the forecasting of the parameters with various changing law.
实例预报结果表明，把自适应指数平滑预报模型应用于灌区需水量预报中是可行的。
The forecasting results of the case study has proved that the adaptive control exponential smoothing forecasting model suits water demand forecast in irrigation districts.
对原有指数平滑法进行市场预测，在此基础上建立了二次指数平滑法的预测模型，进而提出了三次指数平滑法的预测模型。
To make market prediction of former index, based on which build the prediction model of two dimension index and then bring about the prediction model of three dimension index.
对统计算法中回归模型中的假设条件、平滑指数的自适应调整、ARMA模型的参数估计作了一些分析。
We make analyses of the three hypotheses of regression. Adaptive adjustment of smoothing index parameters and parameter estimation of ARMA models.
通过噪声带宽分别衡量不同指数平滑预测模型引起供应链库存波动的程度，并且通过匹配滤波的方法可以减少不同预测模型引起供应链的波动性。
The extent of inventory fluctuating induced by different smoothing forecasting model can be measured by noise bandwidth, and the inventory fluctuating can be reduced by matched filtering.
改进后的指数加权平滑模型的参数是随着参数变化规律的变化而变化的，这种预报模型具有自适应的特点。
The model parameter of the improved exponent weighted gliding average model varies with the change of the law of the forecasted parameter.
最后，建立了基于时间序列的二次指数平滑线性预测模型，进行商品销售趋势的分析，部分验证了本文的设计分析。
Finally built a two linear forecasting models based on smoothing of time queue about analysis of sale trend, and verified the design analysis of this paper partly.
而作为其重要分支之一的指数平滑法，因为操作简单、适用性强、性能优良、应用广泛而成为经典的预测与控制模型。
Exponential smoothing, as a key branch of time series, is a typical forecasting and control model. Because the model have some merit characteristics and wide application.
本文构建了测定职业经理市场供给状况的指标体系，运用指数平滑移动法对市场中职业经理收入进行了预测分析，并利用线性回归预测模型对职业经理市场供给进行了研究；
The smoothing and moving method to predict the managers' income in the market is anticipated and analyzed. A linear regression prediction model to study the supply of the manager market is studied.
本文通过实地调查获取的交通流量数据，分别采用移动平均法、指数平滑法、AR模型法三种交通流预测方法进行短时交通流量预测。
Through the data obtained by fieldwork, the paper forecasts the short-term traffic by three methods: moving-average method, index-smoothing method, AR model method.
本文通过实地调查获取的交通流量数据，分别采用移动平均法、指数平滑法、AR模型法三种交通流预测方法进行短时交通流量预测。
Through the data obtained by fieldwork, the paper forecasts the short-term traffic by three methods: moving-average method, index-smoothing method, AR model method.
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