A methodology to train and improve artificial neural networks' weights and connections. Zanchettin, C. & Ludermir, T. In IEEE International Conference on Neural Networks - Conference Proceedings, 2006. abstract bibtex This work presents a new methodology that integrates the heuristics tabu search, simulated annealing, genetic algorithms and backpropagation in a prunning and constructive way. The approach obtained promising results in the simultaneous optimization of artificial neural network architecture and weights. The experiments were performed in four classification and one prediction problem. © 2006 IEEE.
@inproceedings{
title = {A methodology to train and improve artificial neural networks' weights and connections},
type = {inproceedings},
year = {2006},
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abstract = {This work presents a new methodology that integrates the heuristics tabu search, simulated annealing, genetic algorithms and backpropagation in a prunning and constructive way. The approach obtained promising results in the simultaneous optimization of artificial neural network architecture and weights. The experiments were performed in four classification and one prediction problem. © 2006 IEEE.},
bibtype = {inproceedings},
author = {Zanchettin, C. and Ludermir, T.B.},
booktitle = {IEEE International Conference on Neural Networks - Conference Proceedings}
}
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