On the Capability of Support Vector Machines to Classify Lithology from Well Logs
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Environmental Science
Link
http://link.springer.com/content/pdf/10.1007/s11053-010-9118-9.pdf
Reference28 articles.
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3. Al-Anazi, A., Gates, I. D., and Azaiez, J., 2009, Fuzzy logic data-driven permeability prediction for heterogeneous reservoirs, in Paper SPE 121159 Presented at the 2009 SPE EUROPEC/EAGE Annual Conference and Exhibition, 8–11 June, Amsterdam, The Netherlands
4. Amari, S., and Wu, S., 1999, Improving support vector machine classifiers by modifying kernel functions: Proc. Int. Conf. Neural Netw., v. 12, p. 783–789.
5. Burges, C. C., 1998, A tutorial on support vector machines for pattern recognition: Proc. Int. Conf. Data Mining Knowl. Discov., v. 2, no. 2, p. 121–167.
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