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。
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 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 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。
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。
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。
The random settlement could be gotten by random prediction model that is established by smooth and stable time series analysis method.
用平稳时间序列分析方法建立随机部分模型，并预测沉降随机部分值，二者之和即为某时期沉降预测值。
The time series analysis can also be used in ship pitching and heaving time series prediction. These indicate that the prediction method is valuable for engineering practice.
时间序列分析法亦可用于船舶纵摇、艏摇的时间序列预报，该方法在工程中具有很大的实用价值。
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。
Finally, connecting embedding theory with prediction errors, we propose a new prediction method to chaotic time series based on embedding technique and prediction errors on tested sets.
最后，结合嵌入理论和预测误差，提出了基于嵌入技术和确定集上预测误差的混沌时序预测方法。
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。
This paper proposes the prediction method of time series based on AR model and forecasts the development trend of weighted length of fiber for hydrocyclone by this method.
以时间序列为理论基础，利用时间序列分析方法对水力旋流器的筛分性能建立了AR模型，并依据该模型对纤维重均长度变化趋势进行了预测分析。
A short-term prediction method developed on the basis of the deterministic chaos theory is used to predict the time series of pressure fluctuations in a gas-liquid bubble column with a single orifice.
应用混沌预测方法，对气液两相单孔鼓泡系统的压力波动时间序列进行了短期预测。
Prediction parameters preprocessing method is proposed which is based on time series analysis with wavelet transform method. And in this way, the prediction accuracy is increased.
提出了基于时间序列分析和小波变换方法的实测参数预处理方法，提高了预测精度。
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。
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。
Compared to the prediction results of time series method, the prediction results of ANN method are of higher precision. The prediction errors varied with seasons.
与随机时间序列分析方法预测结果比较，神经网络方法可以提高预测精度，预测误差也呈现出随季节发生变化的规律。
In this paper, the traditional echo state network (ESN) through the structure and learning mechanism of the study, on the echo state network prediction method of chaotic time series.
本文主要通过对传统回声状态网络(esn)的结构和学习机理的研究，探讨了回声状态网络对混沌时间序列的预测方法。
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。
Thus, the chaotic analytic method is set up for the prediction of the measured displacement time series of rock mass engineering.
据此，建立了岩体工程位移观测数据的混沌预测方法。
This paper proposes an improved adding-weight one-rank local-region method for prediction 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。
Based on the prediction method of univariate time series, and according to the proper selection of dimension and delay time, the time series can be predicted precisely.
根据单变量时间序列的混沌预测方法，只要嵌入维数和延迟时间选择得合理，便能进行精确的预测。
The method of predicting time series and the method of improving the accuracy of prediction were studied.
研究时序数据预报和提高预报精度的方法。
Conclusions Moving seasonal mean ratio method could consider secular, seasonal, cyclic and random tendencies of time-series data together and could serve as a useful tool for prediction.
结论移动平均比率法综合考虑长期、季节、周期及随机趋势，预测效果较好。
This thesis studies on the prediction modeling method of water quality parameters based on normal time-series data in the background of the Three Gorges Reservoir.
本文以三峡库区常态水质参数时序数据为研究对象，进行水质参数预测建模研究。
This thesis studies on the prediction modeling method of water quality parameters based on normal time-series data in the background of the Three Gorges Reservoir.
本文以三峡库区常态水质参数时序数据为研究对象，进行水质参数预测建模研究。
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