In this paper, the theory of gray system is adopted to study the time series prediction of the leaching rate of in-situ blasting and leaching ore.
采用灰色系统理论对原地爆破浸出率的时间序列预测问题进行了研究。
This paper inserts grey system, makes use of finite time series, follows GM (1, 1) building method, builds the long term prediction model of total waste -water in Heilongjiang Province.
本文引入灰色系统理论,利用有限的时间序列,按照GM(1,1)建模方法,建立起黑龙江省污水总量长期预测模型。
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。
The prediction method of weight local basis function is presented based on the deep research on local prediction for chaotic time series.
在深入研究混沌时间序列局域预测方法的基础上,提出了一种加权局域基函数预测方法。
During this course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction.
课程期间我们将检视数种学习技巧在一些领域上的应用如电脑视觉、电脑绘图、数据库搜索和时间数列分析与预测。
While applying the method to the time series data of sedimentary rock in Talimu basin, the prediction and classification of layer in petroleum well have got solution.
在塔里木盆地沉积岩时间序列化学数据的应用实例中,解决了石油井下地层预测和归类问题。
Then, we make prediction with moving exponential average model after the analysis of the travel time series. Finally, we present reasonable justification.
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。
By means of it, we could get the quantitative method to measure the intrinsic prediction complexity of time series.
这一概念是对线性偏自相关的一般化,由它可以得到度量时间序列预测复杂性的定量方法。
Finally, the results show the methods can effectively come into being regression analysis model of time-series data streams, and fulfill the prediction of future data streams.
最后,试验分析展示了研究结果能够有效地产生时间序列数据流的回归模型和实现数据流未来数据的预测。
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。
A method of stock price prediction is presented by hypothesis of stock market being non-linear dynamic system and analyzing method of chaos theory for chaos time series in this paper.
根据股票市场是非线性动力系统的假设,利用混沌理论对混沌时间序列的分析方法,提出了股票价格预测方法。
For the features of disc proportioning system's lag and discharge rate's fluctuation, applying time series analysis, a disc discharge rate prediction model based on ar model was set up.
针对原料场圆盘配料系统下料量检测滞后和料量随堆料机进退变化较大的特点,应用时间序列分析方法建立了基于AR模型的圆盘下料量预测模型。
The simulation results from function fitting and time series prediction indicate that UGEP performs better than other similar algorithms in each of experimental.
试验结果也证明,在求解函数拟合和时间序列预测等实际问题时,对比同类算法,UGEP算法体现出了较大的优越性。
The Dynamic time series period analysis and prediction model analyses a serial-typed time series from the point of statistics, finding out the law. thereby succeeding in predicting the future.
动态时间序列周期分析预测模型是从数理统计的角度对值为连续型的时间序列进行分析,发现规律,从而成功预测未来。
Based on this, the average predictable size and the longest predictable size of chaotic time series are provided in this paper to definite the time range of short-term prediction.
基于此,给出了混沌时间序列的平均可预测尺度及最长可预测尺度,以此来界定短期预测的时间范围。
The concept is the generalization of partial autocorrelation. By means of it, we could get the quantitative method to measure the intrinsic prediction complexity of time series.
这一概念是对线性偏自相关的一般化,由它可以得到度量时间序列预测复杂性的定量方法。
The prediction of stock market based on the artificial neural network has almost the same precision as that based on time series models.
通过人工神经网络得到的预测结果基本上与较传统的时间序列理论得到的预测结果精度相似。
Based on the time series, a model of linear artificial neural network is set and used for dynamic prediction of discharge of groundwater.
根据其时间序列,建立线性神经网络模型,并将其用于地下水流量的动态预测。
In the second part, the chaotic prediction models for hydrological time series are studied in terms of the chaotic characteristics of hydrological evolution process.
第二部分基于水文序列变化的混沌特性,对水文时间序列的混沌预测模型进行了研究。
A method of chaotic time series prediction problem based on local dynamical similarity is proposed.
基于混沌系统局部特征,提出了一种局部动力相似的混沌时间序列的预测方法。
During the filling construction of the roadbed the total settlement value could be predicted by using time series equal interval prediction model of recent information.
在路基填筑施工过程中,根据沉降观测数据用时间序列分析方法建立等维信息动态预测模型。
Time series analysis based on neural networks theory cross through traditional frame of subjective model draw out prediction on the inner rules of linear time series data.
基于前向型神经网络理论的时间序列分析跳出了传统的建立主观模型的局限,通过时间序列的内在规律作出分析与预测。
Exponential curve was employed in studying time series of typhoid and paratyphoid (1997-2003) and incidence rate of year 2004 was predicted based on the prediction model.
对伤寒、副伤寒发病率时间序列(1997 ~ 2003)采用指数曲线拟合,并对2004年伤寒、副伤寒疫情作出预测。
The LMBP neural network can predict nonlinear time series very well and the new method is effective for the fault prediction of nonlinear systems.
基于该网络的时间序列预测模型可以实现性能优越的非线性预报器,将其应用于非线性系统的故障预报能够取得良好的效果。
Time series analysis is a branch of statistics and widely used in trend prediction.
时间序列分析是统计学的一个重要分支,灰色系统理论是一种动态趋势预测理论。
Through analyzing the field deformation data of supporting structures, the prediction can be gained by time series model so as to guarantee the safety.
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。
Using time series analysis methods, in this paper the prediction model of the epidemic encephalomyelitis in Heilongjiang Province were given.
本文用时间序列分析法建立了黑龙江省流脑预测模型。
Based on the idea of data parallelism, a parallel training model for RBF (radial basis function) neural network in time-series prediction to improve the training speed is proposed.
根据数据并行的思想,提出了在时序预测中并行训练神经网络的模型,以提高训练速度。
Combining Projection Pursuit(PP) and highdimensional time series analysis, the synthetic earthquake prediction model of highdimensional PP time series is built.
将投影寻踪(PP)与高维时间序列分析结合起来,建立了地震PP综合预测模型。
Combining Projection Pursuit(PP) and highdimensional time series analysis, the synthetic earthquake prediction model of highdimensional PP time series is built.
将投影寻踪(PP)与高维时间序列分析结合起来,建立了地震PP综合预测模型。
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