Seasonal-Trend decomposition based on Loess + Machine Learning: Hybrid Forecasting for Monthly Univariate Time Series.
Gabriel Dalforno SilvestreMoisés Rocha dos SantosAndré C. P. L. F. de CarvalhoPublished in: IJCNN (2021)
Keyphrases
- machine learning
- short term
- multivariate time series
- financial time series
- turning points
- weather forecasting
- moving average
- arma model
- forecasting accuracy
- anchovy catches
- autoregressive integrated moving average
- long term
- arima model
- exponential smoothing
- stock market
- decision trees
- learning algorithm
- grey model
- chaotic time series
- machine learning methods
- phase space reconstruction
- natural language processing
- rainfall forecasting
- artificial intelligence
- forecasting model
- hybrid model
- knowledge acquisition
- exchange rate
- pattern recognition
- quasi periodic
- support vector regression
- short term prediction
- knowledge representation
- machine learning algorithms
- computational intelligence
- garch model
- text classification
- medium term
- computer science
- data analysis
- inductive learning
- neural network
- feature selection
- phase space
- machine learning approaches
- autoregressive
- dynamic time warping
- learning tasks
- knowledge discovery