A machine learning approach for forecasting hierarchical time series.
Paolo MancusoVeronica PiccialliAntonio Maria SudosoPublished in: CoRR (2020)
Keyphrases
- weather forecasting
- financial time series
- forecasting accuracy
- exponential smoothing
- short term
- arma model
- box jenkins
- chaotic time series
- forecasting model
- stock market
- hierarchical structure
- multivariate time series
- bp neural network
- dynamic time warping
- non stationary
- data mining
- demand forecasting
- turning points
- sequential data
- hybrid model
- prediction model
- coarse to fine
- neural network model
- database
- hierarchical classification
- hierarchical structures
- symbolic representation
- stock price
- support vector regression
- arima model
- medium term
- multiresolution
- autoregressive integrated moving average