( en | de | ru )

 

Disambiguation of "Peregrín, Antonio"

Author of the publication

copydeleteadd this publication to your clipboard
A Review of Distributed Data Models for Learning.

, , , and . HAIS, volume 10334 of Lecture Notes in Computer Science, page 88-97. Springer, (2017)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Peregrin Zistler

Antonio Pinto

Antonio Bergua

Antonio Accardi

Antonio Dell'Aquila

 

Other publications of authors with the same name

Rule Base and Inference System Cooperative Learning of Mamdani Fuzzy Systems with Multiobjective Genetic Algorithms., , and . IFSA/EUSFLAT Conf., page 1045-1050. (2009)Cooperation between the Inference System and the Rule Base by Using Multiobjective Genetic Algorithms., , and . HAIS, volume 5271 of Lecture Notes in Computer Science, page 739-746. Springer, (2008)A view of High Dimensional, Large-Scale and Big Data Fuzzy Rule based Regression and Control Systems., , , and . FUZZ-IEEE, page 1-6. IEEE, (2018)A Review of Distributed Data Models for Learning., , , and . HAIS, volume 10334 of Lecture Notes in Computer Science, page 88-97. Springer, (2017)Characterisation of implication operators in fuzzy rule based systems from basic properties., , and . EUSFLAT-ESTYLF Joint Conf., page 163-166. Universitat de les Illes Balears, Palma de Mallorca, Spain, (1999)Parallel evolutionary multiobjective methodology for granularity and rule base learning in linguistic fuzzy systems., , , and . FUZZ-IEEE, page 1700-1705. IEEE, (2009)An efficient multi-objective evolutionary adaptive conjunction for high dimensional problems in linguistic fuzzy modelling., , and . FUZZ-IEEE, page 1-8. IEEE, (2012)Efficient Distributed Genetic Algorithm for Rule Extraction., and . HIS, page 531-536. IEEE Computer Society, (2008)A methodology to generate compact and accurate fuzzy knowledge bases based on fuzzy clustering and evolutionary selection and tuning., , and . FUZZ-IEEE, page 1-7. IEEE, (2010)An Evolutionary Ensemble-Based Method for Rule Extraction with Distributed Data., , and . HAIS, volume 5572 of Lecture Notes in Computer Science, page 638-645. Springer, (2009)