Description of RANNs and their generalisation capabilities by means of rule extraction by genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{conf/asc/GestalRDP06,

• title = "Description of {RANNs} and their generalisation capabilities by means of rule extraction by genetic programming",
• author = "Marcos Gestal and Juan R. Rabu{\~n}al and Julian Dorado and Javier {Pereira Loureiro}",
• booktitle = "Artificial Intelligence and Soft Computing",
• publisher = "IASTED/ACTA Press",
• year = "2006",
• editor = "Angel P. Del Pobil",
• ISBN = "0-88986-612-0",
• pages = "323--328",
• address = "Palma de Mallorca, Spain",
• month = aug # " 28-30",
• bibdate = "2007-01-26",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/asc/asc2006.html#GestalRDP06",
• keywords = "genetic algorithms, genetic programming, Recurrent Artificial Neural Networks, Rule Extraction, Algorithm of Example Generation, Generalisation Capabilities, Series Prediction",
• URL = "http://www.actapress.com/PaperInfo.aspx?PaperID=28200",
• URL = "http://sabia.tic.udc.es/sabia/secciones/publications/?id=311",
• abstract = "Artificial Neural Networks have achieved satisfactory results in different fields such as example classification or image identification. Real-world processes usually have a temporal evolution, and they are the type of processes where Recurrent Networks have special success. Nevertheless they are still reluctantly used, mainly due to the fact that they do not adequately justify their response. But, if ANNs offer good results, why giving them up? Suffice it to find a method that might search an explanation to the outputs that the ANN provides. This work presents a technique, totally independent from ANN architecture and the learning algorithm used, which makes possible the justification of the ANN outputs by means of expression trees.",

}

Genetic Programming entries for Marcos Gestal Pose Juan Ramon Rabunal Dopico Julian Dorado Javier Pereira Loureiro

Citations