On the basis of reviewing numerous existing methods for prediction of oil production, a multimodel adaptive prediction method is developed.
在总结前人大量的产量预测方法的基础上，提出了多模型自适应产量预测方法。
A new algorithm for adaptive prediction error filter is presented.
本文提出一种自适应预测滤波器的新算法。
This method derives from the single-model adaptive prediction technique.
该方法是单模型自适应预测技术的自然推广。
This paper studies an adaptive filter with adaptive prediction pre-processing in the primary input.
本文研究了一种对当输入端进行自适应预测预处理的自适应滤波器。
An approach for lossless compression of still images based on fuzzy-combined adaptive prediction was proposed.
提出了一种基于自适应模糊混合预测的静态图像无损压缩方法。
In regard to stochastic and suddenly varying data, a new kind of data processor algorithm based on adaptive prediction is presented.
对于随机突变参量的数据可靠性处理，本文提出了一种新的基于自适应预报的数据处理器算法。
This paper presents an adaptive prediction coding scheme for the image signals regarded as a high order nonstationary Markov process.
本文把图象信号作为一个高阶非稳马尔柯夫过程，提出一种自适应预测编码方案。
Considering a temperature control system with great delay and model slow changes, a new adaptive prediction control scheme is presented in this paper.
针对一类具有大滞后及模型慢时变的温度控制系统，提出了一种自适应预测控制方案。
In this paper, a lossless compression method, based on adaptive prediction, is presented. This method USES neural network model to modify the prediction weight.
本文提出一种基于自适应预测的无损压缩方法，该方法利用神经网络模型自学习的能力，自适应的调整预测器的预测系数。
This paper develops a novel multilayer neural networks based on adaptive prediction technique for a class of nonlinear dynamical systems, and the prediction mechanism is analyzed .
针对一类非线性动态系统，提出了一种新的基于多层神经网络的自适应预测器，并对基于神经网络的预测机理进行了分析。
Experimental results show that the proposed Volterra adaptive prediction model is capable of effectively predicting traffic flow time sequence and low-dimensional chaotic time sequence.
结果表明，该模型能够较准确地预测交通流量时间序列和低维混沌时间序列。
Experimental results show that the proposed Volterra adaptive prediction model is capable of effectively predicting traffic flow time sequence and low-dimensional chaotic time sequence.
结果表明，该模型能够较准确地预测交通流量时间序列和低维混沌时间序列。
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