multivariable time series forecasting model 多变量时间序列预测模型
Aim To construct a new time-series forecasting model based on neural network with the capability of noise immunity.
目的建立一种新的具有抗噪声能力的神经网络时间序列预测模型。
In the final chapter, we mine stock trading data using time series method, find out the model and outliers in the data and, at last, we show the more exact forecasting model and outlier mining method.
第五章利用时间序列的方法对证券交易数据进行了挖掘，找出了数据中的模式和异常，相对传统方法而言，给出了更精确的预测模型和异常挖掘方法。
In this paper, the numerical solution of differential equation is employed to establish the forecasting model of the time series.
本文利用微分方程的数值解法对时间序列建模预测作了新的尝试。
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