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arimafinal
- 用ARMA模型对时间序列进行预测，预测效果相对于移动平均预测较好，能进行有效预测。-Using the ARMA model to forecast the time sequence, better prediction effect relative to the moving average forecast, can effectively forecast.
FunctionChaosPredict
- 利用一阶局域加权法进行混沌时间序列的预测。-Using a weighted-rank local-region method of forecasting chaotic time series.
elmen网络代码
- ELMAN神经网络模型预测精度高于BP神经网络，可以用于非线性时间序列的预测。(The prediction accuracy of ELMAN neural network model is higher than that of BP neural network, and it can be used to predict nonlinear time series.)
LSTM-for-time-series-prediction
- 本代码是使用lstm进行时间序列预测，能够很清晰的说明如何使用lstm(Time series prediction using LSTM)