运用时间序列预测法对环渤海地区主要航线的客(车)运量进行了预测;
The prediction was made in the volume of ferry in main routes by Time Sequence Prediction method.
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。
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.
将小波分析理论、灰色预测理论和时间序列预测法组合进行需水量的预测,为原始非平稳时间序列的预测应用拓展了空间。
The space of prediction and application of non-stationary time series were expanded through the combined model of wavelet analysis, gray and time series prediction methods.
应用时间序列法对厦门城市日供水量进行预测和误差分析,具有较强的实用价值。
The time sequence method which is quite valuable for use, is applied to the forecast and error analysis of daily water supply amount in Xiamen City.
通过现场量测的深基坑围护结构变形信息资料,对数据进行整理和分析,利用时间序列分析法对支护结构的变形作出预测,以保证基坑安全施工。
Through analyzing the field deformation data of supporting structures, the prediction can be gained by time series model so as to guarantee the safety.
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。
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.
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 time series analysis is proposed for load forecasting of power-generating and power transmission programming in power systems.
采用时间序列分析法对某型飞机的故障率进行预测,其结果可为可靠性维修提供理论依据。
The results from time array analysis to predict failure of an aircraft can provide theory basis for the reliability maintenance.
以水均衡方程为基础,应用时间序列分析法,建立系统管理模型,对地下水资源系统进行系统运行控制、预测和管理。
Systematic management model is set up by time series analytic method based on water balance equation to control, predict and manage groundwater resources system.
第四章运用时间序列法对国内加油机市场未来五年的市场容量进行预测。
In chapter four, time sequence method was used to forecast the market capacity of domestic dispenser industry in coming five years.
针对混沌时间序列的最近邻域预测法,提出了改进的最近邻域点优化选择方法和加权一阶局域线性预测法。
Optimal choice method of the nearest neighboring points and adding weight one-rank local region method is introduced on the nearest neighboring forecasting method of chaotic time series.
提出了一种用于混沌时间序列预测的改进型加权一阶局域法。
This paper proposes an improved adding-weight one-rank local-region method for prediction of chaotic time series.
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。
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.
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。
Conclusion: The exponential smoothing method could be employed to forecast a time series of one dimension for cucumber downy disease.
实例分析表明,相对于单嵌入维数法,多嵌入维数组合预测方法可以综合利用不同相空间中的有用信息,提高径流时间序列预测的精度。
The results of actual runoff prediction show that the proposed method could use information synthetically in multi-dimension embedding phase spaces, and effectively improve the prediction accuracy.
本文用时间序列分析法建立了黑龙江省流脑预测模型。
Using time series analysis methods, in this paper the prediction model of the epidemic encephalomyelitis in Heilongjiang Province were given.
温特斯法可以对具有随机性、线性、季节性变化的时间序列进行预测,用温特斯法作了一次温度预测尝试。
The Winters method can be used to predict the time series that is of randomicity, linearity and(seasonal) variation.
尝试用时间序列分析中的自适应滤波法对江河灾害性洪水进行预测,认为加权因子个数和自适应常数的确定是关键。
Adaptive filtering in time series analysis is used to predict a stream flood. The key in this process is determination of the adaptive constants and the number of weighted factors.
回归分析法、弹性系数法、时间序列法等是市场预测中常用的方法。
Regression analysis law , Resilience factor law , The time queue law awaits the means being in common use in the market forecast.
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。
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.
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。
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。
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.
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