The Use of Artificial Neural Network and Support Vector Classification for Recovery Factor Prediction
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Li Dawei | Guangren Shi | L. Dawei | G. Shi
[1] Isam Shahrour,et al. Use of artificial neural network simulation metamodelling to assess groundwater contamination in a road project , 2007, Math. Comput. Model..
[2] Guangren Shi. Data Mining and Knowledge Discovery for Geoscientists , 2013 .
[3] D.R. Hush,et al. Progress in supervised neural networks , 1993, IEEE Signal Processing Magazine.
[4] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[5] Wan Jun,et al. A Big Data Mining in Petroleum Exploration and Development , 2014 .
[6] Daniel T. Larose,et al. Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .
[7] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[8] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[9] P. Khadikar,et al. Comparative QSAR Study on Para‐substituted Aromatic Sulphonamides as CAII Inhibitors: Information versus Topological (Distance‐Based and Connectivity) Indices , 2008, Chemical biology & drug design.
[10] Jian Pei,et al. Data Mining : Concepts and Techniques 3rd edition Ed. 3 , 2011 .
[11] G. Shi. Optimal Prediction in Petroleum Geology by Regression and Classification Methods , 2015 .
[12] Xin-She Yang,et al. Optimization and data mining for fracture prediction in geosciences , 2010, ICCS.
[13] Robert Hecht-Nielsen,et al. Theory of the backpropagation neural network , 1989, International 1989 Joint Conference on Neural Networks.
[14] Refik Soyer,et al. Bayesian Methods for Nonlinear Classification and Regression , 2004, Technometrics.
[15] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[16] G. Shi,et al. The use of artificial neural network analysis and multiple regression for trap quality evaluation: a case study of the Northern Kuqa Depression of Tarim Basin in western China , 2004 .
[17] Fulya Altiparmak,et al. Buffer allocation and performance modeling in asynchronous assembly system operations: An artificial neural network metamodeling approach , 2007, Appl. Soft Comput..
[18] Zhang Qian,et al. Economic Evaluation of Waterflood Using Regression and Classification Algorithms , 2015 .
[19] David J. Crisp,et al. A Geometric Interpretation of ?-SVM Classifiers , 1999, NIPS 2000.
[20] Deok-Hwan Kim,et al. Solving local minima problem with large number of hidden nodes on two-layered feed-forward artificial neural networks , 2008, Neurocomputing.
[21] Seung-Han Yang,et al. Statistical optimization and assessment of a thermal error model for CNC machine tools , 2002 .
[22] Seyyed Mohsen Salehi,et al. Automatic Identification of Formation Iithology from Well Log Data: A Machine Learning Approach , 2014 .
[23] Pedro M. Domingos,et al. On the Optimality of the Simple Bayesian Classifier under Zero-One Loss , 1997, Machine Learning.
[24] G. Shi,et al. Optimal Selection of Classification Algorithms for Well Log Interpretation , 2015 .
[25] G. Shi. Prediction of Methane Inclusion Types Using Support Vector Machine , 2015 .
[26] Elif Derya Übeyli,et al. Detection of ophthalmic artery stenosis by least-mean squares backpropagation neural network , 2003, Comput. Biol. Medicine.
[27] Arjun K. Gupta,et al. Bayesian discrimination using multiple observations , 1993 .
[28] M. Kenward,et al. Bayesian discrimination with longitudinal data. , 2001, Biostatistics.
[29] Helmy Sayyouh,et al. An Integrated Approach for the Application of the Enhanced Oil Recovery Projects , 2014 .
[30] Bernhard Schölkopf,et al. New Support Vector Algorithms , 2000, Neural Computation.
[31] Bernhard E. Boser,et al. A training algorithm for optimal margin classifiers , 1992, COLT '92.
[32] Chih-Jen Lin,et al. Manuscript Number: 2187 Training ν-Support Vector Classifiers: Theory and Algorithms , 2022 .
[33] Li Dawei,et al. Data Mining in Petroleum Upstream ——The Use of Regression and Classification Algorithms , 2015 .
[34] Guang-Ren Shi,et al. The use of support vector machine for oil and gas identification in low-porosity and low-permeability reservoirs , 2009, Int. J. Math. Model. Numer. Optimisation.