Neural networks with multiple general neuron models: A hybrid computational intelligence approach using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Barton2009614,

• author = "Alan J. Barton and Julio J. Valdes and Robert Orchard",
• title = "Neural networks with multiple general neuron models: A hybrid computational intelligence approach using Genetic Programming",
• journal = "Neural Networks",
• volume = "22",
• number = "5-6",
• pages = "614--622",
• year = "2009",
• note = "Advances in Neural Networks Research: IJCNN2009, 2009 International Joint Conference on Neural Networks",
• editor = "S. Bressler and R. Kozma and L. Perlovsky and Venayagamoorthy",
• keywords = "genetic algorithms, genetic programming, General neuron model, Evolutionary Computation, Hybrid algorithm, Machine learning, Parameter space, Visualization",
• ISSN = "0893-6080",
• DOI = "doi:10.1016/j.neunet.2009.06.043",
• URL = "http://www.sciencedirect.com/science/article/B6T08-4WNRK15-3/2/d8803b07859caa7efcd99475af7005ae",
• abstract = "Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.",

}

Genetic Programming entries for Alan J Barton Julio J Valdes Robert Orchard

Citations