Investigating the effect of correlation-based feature selection on the performance of support vector machines in reservoir characterization
暂无分享,去创建一个
[1] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[2] Andrew McCallum,et al. Efficient clustering of high-dimensional data sets with application to reference matching , 2000, KDD '00.
[3] Xiaoou Li,et al. Support vector machine classification for large data sets via minimum enclosing ball clustering , 2008, Neurocomputing.
[4] Michael D. Tusiani,et al. LNG: A Nontechnical Guide , 2007 .
[5] Tom Gedeon,et al. A STATE-OF-THE-ART REVIEW OF NEURAL NETWORKS FOR PERMEABILITY PREDICTION , 2000 .
[6] Federico Girosi,et al. Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[7] Ali Selamat,et al. Predicting correlations properties of crude oil systems using type-2 fuzzy logic systems , 2011, Expert Syst. Appl..
[8] Xiaoou Li,et al. Fast Support Vector Machine Classification for Large Data Sets , 2014, Int. J. Comput. Intell. Syst..
[9] Wasfi G. Al-Khatib,et al. Identification of Question and Non-Question Segments in Arabic Monologues Using Prosodic Features: Novel Type-2 Fuzzy Logic and Sensitivity-Based Linear Learning Approaches , 2013 .
[10] Walter Rose,et al. Some Theoretical Considerations Related To The Quantitative Evaluation Of The Physical Characteristics Of Reservoir Rock From Electrical Log Data , 1950 .
[11] P. H. Nelson,et al. Permeability Prediction From Well Logs Using Multiple Regression , 1986 .
[12] Feng Li,et al. An Efficient Hierarchical Clustering Method for Large Datasets with Map-Reduce , 2009, 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies.
[13] Ali Selamat,et al. Improved sensitivity based linear learning method for permeability prediction of carbonate reservoir using interval type-2 fuzzy logic system , 2014, Appl. Soft Comput..
[14] W. D. Carrier. Goodbye, Hazen; Hello, Kozeny-Carman , 2003 .
[15] Tixier Maurice Pierre. Evaluation of permeability from electric-log resistivity gradient , 1949 .
[16] Ali Selamat,et al. A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction , 2014, Inf. Fusion.
[17] Masoud Nikravesh,et al. Soft Computing for Reservoir Characterization and Modeling , 2010 .
[18] Morteza Ahmadi,et al. Design of neural networks using genetic algorithm for the permeability estimation of the reservoir , 2007 .
[19] Hossain Arif,et al. IDENTIFICATION OF ERYTHEMATO-SQUAMOUS SKIN DISEASES USING EXTREME LEARNING MACHINE AND ARTIFICIAL NEURAL NETWORK , 2013, SOCO 2013.
[20] G. R. Coates,et al. Permeability estimation; The various sources and their interrelationships , 1991 .
[21] Sunday O. Olatunji,et al. Performance Comparison of SVM and ANN in Predicting Compressive Strength of Concrete , 2014 .
[22] Sunday O. Olatunji,et al. Estimation of Superconducting Transition Temperature TC for Superconductors of the Doped MgB2 System from the Crystal Lattice Parameters Using Support Vector Regression , 2015 .
[23] Alexandros Labrinidis,et al. Challenges and Opportunities with Big Data , 2012, Proc. VLDB Endow..
[24] David R. Lamb,et al. Statistics and research in physical education , 1970 .
[25] Jason W. Osborne,et al. The power of outliers (and why researchers should ALWAYS check for them) , 2004 .
[26] Kathleen M. MacQueen,et al. Handbook for Team-Based Qualitative Research , 2007 .
[27] Kabiru O. Akande,et al. Support Vector Machines Approach for Estimating Work Function of Semiconductors: Addressing the Limitation of Metallic Plasma Model , 2014 .
[28] Sylvain J. Pirson,et al. Handbook of well log analysis : for oil and gas formation evaluation , 1963 .
[29] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[30] Djebbar Tiab,et al. Application of artificial intelligence to characterize naturally fractured zones in Hassi Messaoud Oil Field, Algeria , 2005 .
[31] D. Stoneking. Improving the manufacturability of electronic designs , 1999 .