01433naa a2200265 a 450000100080000000500110000800800410001910000200006024501060008026000090018652006790019565000130087465000200088765000140090765000140092165300140093565300120094965300180096170000200097970000200099970000260101970000150104570000200106077300870108020847802020-01-07       2017    bl uuuu     u00u1 u    #d1 aFERREIRA, L. M.  aApplication of artificial neural networks in the simulation with genetic data.h[electronic resource]  c2017  aAbstract: The objective of this work was the concept of applying artificial neural networks in the study of genetic data, in order to make the identification of the microsatellite markers for a particular species of plant to be analyzed more efficient. In this study, was used as an experimental model the data generated for 26 grapevine genotypes were divided into the following populations: Vitis vinifera; North American varieties; and intersp ecific hybrid of rootstocks. After the network training was carried out, an error rate of 0.0003460 was obtained, concluding that the network was able to learn according to the type of data used, even when these data are small.  aGenotype  aNeural networks  aGenética  aGenótipo  aGrapevine  aNetwork  aRedes neurais1 aSILVA, J. de A.1 aSANT'ANA, G. C.1 aCANÇADO, G. M. de A.1 aBORÉM, A.1 aFERREIRA, J. L.  tInternational Journal of Engineering Inventionsgv. 6, n. 12, p. 43-46, Dec. 2017.