Genetic Programming in Time Series Modelling: An Application to Meteorological Data (2001)
by
Katya Rodriguez Vazquez
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Abstract:
. This paper describes a genetic programming approach for applications on prediction of real meteorological data. The well-know SISO NARMAX model is used to model and forecast this real time series. The evaluation of candidate models is based on a set of criteria taken into consideration in order to get the simpler and more accurate model for prediction. 1.
Citations
| 54 | Input--output parametric models for non--linear systems: Part I: deterministic non--linear systems – Leontaritis, Billings - 1985 |
| 9 | Representation of nonlinear systems – S, Billings - 1989 |
| 8 | Non-linear Model Term Selection with Genetic Algorithms – Fonseca, Mendes, et al. - 1993 |
| 1 | Least Square Parameter Estimation Algorithm for Non-Linear Systems – BILLINGS, VOON - 1984 |
| 1 | Multi-Objective Genetic Programming: A Non-linear System Identification Application. Late Breaking Paper at the GP’97 Conference – FLEMING - 1997 |
| 1 | MultiObjective Genetic Programming for a Gas Turbine Engine Model Identification – RODRÍGUEZ-VÁZQUEZ, FLEMING - 1998 |

