Title: An intelligent oil reservoir identification approach by deploying quantum Levenberg-Marquardt neural network and rough set
Authors: Nanping Liu, Fei Zheng, Kewen Xia
Addresses: School of Information, Hebei University of Technology, Tianjin 300401, China; College of Physics and Electronic Information, Tianjin Normal University, Tianjin 300387, China. ' School of Information, Hebei University of Technology, Tianjin 300401, China. ' School of Information, Hebei University of Technology, Tianjin 300401, China; Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Abstract: An intelligent identification approach combining the features of parallel computation of quantum Levenberg-Marquardt neural network (Q-LM-NN) and information reduct of rough set is proposed as an improved alternative to common statistical identification methods and single-intelligent-based methods which are unable to attain satisfactory result in engineering applications. This approach has been tested to have better performance on reducing the cost and improving the identification accuracy than other methods in practical oil log applications.
Keywords: quantum LM neural networks; Q-LM-NN; reservoir identification; quantum computing; rough sets; oil reservoirs; intelligent identification; parallel computing; oil log applications.
International Journal of Computational Science and Engineering, 2011 Vol.6 No.1/2, pp.76 - 85
Published online: 13 Jul 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article