Abstract
In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on statistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model selection criteria and tests. Mis-specification tests for evaluating an estimated neural network model are considered. Forecasting with neural network models is discussed and an application to a real time series is presented.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 227-235 |
| Number of pages | 9 |
| Journal | International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications |
| Volume | 9 |
| Issue number | 4 |
| State | Published - Dec 2001 |
| Externally published | Yes |
Keywords
- Model mis-specification
- Neural computing
- Nonlinear forecasting
- Nonlinear time series
- Smooth transition autoregression
- Sunspot series
- Threshold autoregression
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering