@inproceedings{358,
  author = {María Dolores Pérez Godoy and Pedro Pérez and Antonio Jesús Rivera Rivas and Maria José del Jesus Díaz and María del Pilar Frías Bustamante and Manuel Parras},
  editor = {Nicolás García-Pedrajas and Francisco Herrera Triguero and Colin Fyfe and Jose Benitez and Moonis Ali},
  title = {Intelligent Systems in Long-Term Forecasting of the Extra-Virgin Olive Oil Price in the Spanish Market},
  abstract = {In this paper the problem of estimating forecasts, for the Official Market of future contracts for olive oil in Spain, is addressed. Time series analysis and their applications is an emerging research line in the Intelligent Systems field. Among the reasons for carry out time series analysis and forecasting, the associated increment in the benefits of the implied organizations must be highlighted. In this paper an adaptation of CO2RBFN, evolutionary COoperative-COmpetitive algorithm for Radial Basis Function Networks design, applied to the long-term prediction of the extra-virgin olive oil price is presented. This long-term horizon has been fixed to six months. The results of CO2RBFN have been compared with other data mining methods, typically used in time series forecasting, such as other neural networks models, a support vector machine method and a fuzzy system.},
  year = {2010},
  pages = {205-214},
  publisher = {Springer Berlin Heidelberg},
  address = {Berlin, Heidelberg},
  isbn = {978-3-642-13022-9},
}