Abstract
This work presents a technique that integrates the heuristics tabu search, simulated annealing, genetic algorithms and backpropagation. This approach obtained promising results in the simultaneous optimization of the artificial neural network architecture and weights.
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Zanchettin, C., Ludermir, T.B. (2005). Hybrid Technique for Artificial Neural Network Architecture and Weight Optimization. In: Jorge, A.M., Torgo, L., Brazdil, P., Camacho, R., Gama, J. (eds) Knowledge Discovery in Databases: PKDD 2005. PKDD 2005. Lecture Notes in Computer Science(), vol 3721. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564126_76
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DOI: https://doi.org/10.1007/11564126_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29244-9
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