@book{
 title = {Hybrid technique for artificial neural network architecture and weight optimization},
 type = {book},
 year = {2005},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 volume = {3721 LNAI},
 id = {d91a0a47-daab-3ea0-9d81-b9b2c8b2b73d},
 created = {2019-02-14T18:02:00.323Z},
 file_attached = {false},
 profile_id = {74e7d4ea-3dac-3118-aab9-511a5b337e8f},
 last_modified = {2019-02-14T18:02:00.323Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 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. © Springer-Verlag Berlin Heidelberg 2005.},
 bibtype = {book},
 author = {Zanchettin, C. and Ludermir, T.B.},
 doi = {10.1007/11564126_76}
}

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