Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition.
Ümit Çavus BüyüksahinSeyda ErtekinPublished in: Neurocomputing (2019)
Keyphrases
- hybrid method
- empirical mode decomposition
- hybrid model
- artificial neural networks
- forecasting accuracy
- absolute percentage error
- non stationary
- bp neural network
- neural network model
- demand forecasting
- hybrid algorithm
- support vector machine
- hilbert huang transform
- neural network
- forecasting model
- multi band
- support vector regression
- computational intelligence
- high dimensional
- genetic algorithm ga
- genetic algorithm
- wavelet decomposition
- back propagation
- short term
- support vector
- eeg signals
- intrinsic mode functions
- computer vision
- data mining
- decision trees
- levenberg marquardt
- multiscale
- evolutionary algorithm