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Abstract: Neural networks and genetic algorithms demonstrate powerful problem solving ability. They are based on quite simple principles, but take advantage of their mathematical nature: non-linear iteration. Neural networks with backpropagation learning showed results by searching for various kinds of functions. However, the choice of the basic parameter (network topology, learning rate, initial weights) often already determines the success of the training process. The selection of these parameter... (Update)
Context of citations to this paper: More
...also Diplomarbeit , Tech. Lic. Theses , etc. University of Edinburgh, 22] University of Erlangen and The University of Tennessee, [122] University of Nebraska Lincoln, 128] University of Vaasa, 278] total 4 thesis in 4 schools 4.4 Report series The following list contains...
...also Diplomarbeit , Tech. Lic. Theses , etc. University of Edinburgh, 24] University of Erlangen and The University of Tennessee, [164] University of Nebraska Lincoln, 23] University of Turku, 126] University of Vaasa, 318] total 5 thesis in 5 schools 4.4 Report series...
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BibTeX entry: (Update)
Philipp Koehn. Combining genetic algorithms and neural networks: The encoding problem. Master's thesis, University of Erlangen and The University of Tennessee, Knoxville, 1994. (available via anonymous ftp site archive.cis.ohio-state.edu directory pub/neuroprose le koehn.encoding.ps.Z) ga94aKoehn. http://citeseer.ist.psu.edu/article/koehn94combining.html More
@misc{ koehn94combining,
author = "P. Koehn",
title = "Combining genetic algorithms and neural networks: The encoding problem",
text = "Philipp Koehn. Combining genetic algorithms and neural networks: The encoding
problem. Master's thesis, University of Erlangen and The University of Tennessee,
Knoxville, 1994. (available via anonymous ftp site archive.cis.ohio-state.edu
directory pub/neuroprose le koehn.encoding.ps.Z) ga94aKoehn.",
year = "1994",
url = "citeseer.ist.psu.edu/article/koehn94combining.html" }
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