Ensemble learning model for petroleum reservoir characterization: A case of feed-forward back-propagation neural networks

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Ensemble learning model for petroleum reservoir characterization: A case of feed-forward back-propagation neural networks

Conventional machine learning methods are incapable of handling several hypotheses. This is the main strength of the ensemble learning paradigm. The petroleum industry is in great need of this new learning methodology due to the persistent quest for better prediction accuracies of reservoir properti...

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Bibliographic Details
Main Authors:	Fatai, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem
Format:	Proceeding
Language:	English
Published:	2013
Subjects:	QE Geology
Online Access:	http://ir.unimas.my/id/eprint/15781/ http://ir.unimas.my/id/eprint/15781/1/Ensemble%20learning%20model%20for%20petroleum%20reservoir%20characterization%20%28abstrak%29.pdf

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