- author = "Leonardo Trujillo and Yuliana Martinez and Patricia Melin",
- title = "How many neurons?: a genetic programming answer",
- booktitle = "GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation",
- year = "2011",
- editor = "Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger",
- isbn13 = "978-1-4503-0690-4",
- keywords = "genetic algorithms, genetic programming, Genetics based machine learning: Poster",
- pages = "175--176",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
-
DOI = "
doi:10.1145/2001858.2001956",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "The goal of this paper is to derive predictive models that take as input a description of a problem and produce as output an estimate of the optimal number of hidden nodes in an Artificial Neural Network (ANN). We call such computational tools Direct Estimators of Neural Network Topology (DENNT), an use Genetic Programming (GP) to evolve them. The evolved DENNTs take as input statistical and complexity descriptors of the problem data, and output an estimate of the optimal number of hidden neurons.",
-
notes = "Also known as \cite{2001956} Distributed on CD-ROM at
GECCO-2011.
ACM Order Number 910112.",
