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PAPER ID: E06
TITLE: Application of genetic algorithms for increase of an overall performance of artificial neural networks
AUTHORS: M. Karpunina
Full paper (4p.)
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QUALITY JUDGEMENT (notes from 1 -poor- to 5 -excellent)
- RELEVANCE TO THE CONFERENCE   : 4
- ORIGINALITY                   : 3
- SCIENTIFIC QUALITY            : 3
- PRESENTATION AND WRITING STYLE: 2
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COMMENTS

The paper deals with the mixing of genetic algorithms and neural networks for the area of synthesis optimum structures of distributed databases.

The formula use too small characters and they are not readable. Thanks to improve the quality of the formula in the final version.

The Figure is not exploitable because the legends are not readable.

A more synthetic approach of the problem could make the paper more accessible to the reader.

However the mixed solver based on neural network and on genetic algorithm seems to be efficient and each part is well-used in function of its specificity.

Thanks to try to improve the quality of reading for the final version, giving some synthetic vison at each step and improving the quality of the typography for the formula and the figure.

Thanks to verify that the document agree with the author consigns given by the general conference IEEE-ICECS 2005 (see on web page)
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ACCEPTATION:  yes
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