Please use this identifier to cite or link to this item:
|Type:||Artigo de evento|
|Title:||Artificial Immune Systems For Classification Of Petroleum Well Drilling Operations|
|Abstract:||This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In order to validate the performance of AIS techniques, the results were compared with others classification methods: neural network, support vector machine and lazy learning. © Springer-Verlag Berlin Heidelberg 2007.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.