How to identify chaos is the foundation of analysis, prediction and control of nonlinear time series.
识别混沌是对非线性时间序列进行分析、预测、控制的基础。
In this paper, using neuron network models of nonlinear multidimensional time series prediction, neuron network predictors for the oil production and water production of oil fields were constructed.
从信息论角度出发，利用神经网络非线性时间序列预测模型，构造了油田产油量、产水量的多维时间序列神经网络预测器。
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。
A new approach to fault diagnosis of nonlinear systems, which USES multistep prediction of time series based on neural network, is presented in this paper.
提出一种新的基于神经网络多步时序预测的非线性系统故障诊断方法。
As a new type of recurrent neural network, echo state network (ESN) is applied to nonlinear system identification and chaotic time series prediction.
ESN(回声状态网络)是一种新型的递归神经网络，可有效处理非线性系统辨识以及混沌时间序列预测问题。
Next, the stock price prediction model is proposed on the base of nonlinear time series prediction theory.
根据部分可量化股价影响因素，选取预测模型的输入变量。
Next, the stock price prediction model is proposed on the base of nonlinear time series prediction theory.
根据部分可量化股价影响因素，选取预测模型的输入变量。
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