@InProceedings{SambattiAnLuCaShCa:2012:MPMeAu,
author = "Sambatti, Sabrina Bergoch Monteiro and Anochi, Juliana Aparecida
and Luz, Eduardo F. Pacheco da and Carvalho, Adenilson R. and
Shiguemori, Elcio Hideiti and Campos Velho, Haroldo Fraga de",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {} and SERPRO and
{Instituto de Estudos Avan{\c{c}}ado (IEAv)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "MPCA Meta-Heuristics for automatic architecture optimization of a
supervised artificial neural network",
booktitle = "Proceedings...",
year = "2012",
organization = "World Congress on Computational Mechanics, 10. (WCCM).",
abstract = "Artificial neural networks (ANN) has been studied intensively, but
there still are many unresolved issues. The search and definition
of an optimal architecture remains a very relevant ANN research
topic. The search space of neural network topology, each point
represents a possible architecture. Associating each point to a
performance level relies on the a priori establishment of some
optimality criterion. Here, a new meta-heuristics, multi-particle
collision algorithm (MPCA) was applied to design an optimum
architecture for a supervised ANN. The MPCA optimization algorithm
emulates a collision process of multiple particles inspired in
processes of a neutron traveling in a nuclear reactor. The
multilayer perceptron (MLP) was the neural network adopted here,
and backpropagation strategy was used for calculating of the
weight of connections to the MLP-NN. The MLP-NN configured by this
optimal or inverse designs was applied to predict the seasonal
mesoscale climate. The dataset for trainning is obtained from
NCEP-NOAA reanalysis and from a metherological model. In order to
reduce the dimension of the search space to find the optimized
ANN, it is considered the following: three activation functions,
up to three hidden layers, and up to 32 neurons per hidden layer.
The comparison is performed between the ANN configuration obtained
by automatic process and another configuration proposed by a human
specialist.",
conference-location = "S{\~a}o Paulo",
conference-year = "2012",
label = "lattes: 2720072834057575 2 SambattiAnLuCaShCa:2012:MPMeAu",
language = "en",
targetfile = "sambatti_mpca.pdf",
urlaccessdate = "13 maio 2024"
}