A Hybrid Semi-linear System for Time Series Forecasting
| Autor: | Cleyton Mário de Oliveira Rodrigues, João Fausto Lorenzato de Oliveira, Emanoel Barreiros, Adauto Trigueiro de Almeida Filho |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Artificial neural network
Series (mathematics) Computer science Computer Science::Neural and Evolutionary Computation Linear system Particle swarm optimization 02 engineering and technology 01 natural sciences 010104 statistics & probability Nonlinear system Task (computing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Autoregressive integrated moving average 0101 mathematics Time series Algorithm |
| Zdroj: | BRACIS |
| DOI: | 10.1109/bracis.2017.23 |
| Popis: | Time series forecasting is a challenging task in machine learning. Each time series may be composed by linear or nonlinear patterns which need to be mapped by techniques such as autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN). This work proposes an evolutionary semi-linear artificial network for time series forecasting. The system selects the best architecture for linear and nonlinear components of the ANN in order to deal with different patterns simultaneously. Particle swarm optimization is used to find suitable architecture and weights. Experiments show that the proposed technique achieved promising results in time series forecasting. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|