메뉴 건너뛰기




Volumn 177, Issue 20, 2007, Pages 4445-4461

Predicting injection profiles using ANFIS

Author keywords

ANFIS; Data quality problems; Grid partition; Petroleum industry; Subtractive clustering

Indexed keywords

DATA QUALITY PROBLEMS; GRID PARTITION; SUBTRACTIVE CLUSTERING;

EID: 34447509469     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2007.03.021     Document Type: Article
Times cited : (99)

References (32)
  • 2
    • 84974743850 scopus 로고
    • Fuzzy model identification based on cluster estimation
    • Chiu S. Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems 2 3 (1994) 267-278
    • (1994) Journal of Intelligent and Fuzzy Systems , vol.2 , Issue.3 , pp. 267-278
    • Chiu, S.1
  • 3
    • 0013391977 scopus 로고    scopus 로고
    • Extracting fuzzy rules from data for function approximation and pattern classification
    • Dubois D., Prade H., and Yager R. (Eds), Springer, Berlin
    • Chiu S. Extracting fuzzy rules from data for function approximation and pattern classification. In: Dubois D., Prade H., and Yager R. (Eds). Chapter 9 in the Fuzzy Information Engineering: A Guided tour of Applications (1997), Springer, Berlin 149-162
    • (1997) Chapter 9 in the Fuzzy Information Engineering: A Guided tour of Applications , pp. 149-162
    • Chiu, S.1
  • 4
    • 0038209390 scopus 로고    scopus 로고
    • Subtractive clustering based modeling of job sequencing with parametric search
    • Demirli K., Cheng S.X., and Muthukumaran P. Subtractive clustering based modeling of job sequencing with parametric search. Fuzzy Sets and Systems 137 2 (2003) 235-270
    • (2003) Fuzzy Sets and Systems , vol.137 , Issue.2 , pp. 235-270
    • Demirli, K.1    Cheng, S.X.2    Muthukumaran, P.3
  • 5
    • 0034559292 scopus 로고    scopus 로고
    • Higher order fuzzy system identification using subtractive clustering
    • Demirli K., and Muthukumaran P. Higher order fuzzy system identification using subtractive clustering. Journal of Intelligent and Fuzzy Systems 9 3-4 (2000) 129-158
    • (2000) Journal of Intelligent and Fuzzy Systems , vol.9 , Issue.3-4 , pp. 129-158
    • Demirli, K.1    Muthukumaran, P.2
  • 6
    • 0347027758 scopus 로고    scopus 로고
    • B. Fritzke, Incremental neuro-fuzzy systems, in: Proc. Application of Soft Computing, SPIE International Symposium on Optical Science, Engineering and Instrumentation, San Diego, 1997, pp. 86-97.
  • 7
    • 32844456242 scopus 로고    scopus 로고
    • M.A. Hassanain, M.M. Reda Taha, A. Noureldin, N. El-Sheimy, Automation of an INS/GPS integrated system using genetic optimization, in: Proc. the 5th International Symposium on Intelligent Automation and Control, Seville, Spain, 2004, pp. 347-352.
  • 8
    • 0345201769 scopus 로고    scopus 로고
    • TANE: an efficient algorithm for discovering functional and approximate dependencies
    • Huhtala Y., Kärkkäinen J., Porkka P., and Toivonen H. TANE: an efficient algorithm for discovering functional and approximate dependencies. The Computer Journal 42 2 (1999) 100-111
    • (1999) The Computer Journal , vol.42 , Issue.2 , pp. 100-111
    • Huhtala, Y.1    Kärkkäinen, J.2    Porkka, P.3    Toivonen, H.4
  • 9
  • 10
    • 34447522880 scopus 로고    scopus 로고
    • J.R. Jang, Frequently asked questions - ANFIS in the fuzzy logic toolbox, .
  • 12
    • 0033104629 scopus 로고    scopus 로고
    • Three machine learning techniques for automatic determination of rules to control locomotion
    • Jonic S., Jankovic T., Gajic V., and Popovic D. Three machine learning techniques for automatic determination of rules to control locomotion. IEEE Transactions on Biomedical Engineering 46 3 (1999) 300-310
    • (1999) IEEE Transactions on Biomedical Engineering , vol.46 , Issue.3 , pp. 300-310
    • Jonic, S.1    Jankovic, T.2    Gajic, V.3    Popovic, D.4
  • 13
    • 34447541053 scopus 로고    scopus 로고
    • S.D. Kaehler, Fuzzy logic tutorial, the newsletter of the Seattle Robotics Society.
  • 14
    • 0036530967 scopus 로고    scopus 로고
    • DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction
    • Kasabov N., and Song Q. DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction. IEEE Transactions on Fuzzy Systems 10 2 (2002) 144-154
    • (2002) IEEE Transactions on Fuzzy Systems , vol.10 , Issue.2 , pp. 144-154
    • Kasabov, N.1    Song, Q.2
  • 15
    • 1542749367 scopus 로고    scopus 로고
    • P. Kennedy, M. Condon, J. Dowling, Torque-ripple minimization in switched reluctant motors using a neuro-fuzzy control strategy, in: Proc. IASTED International Conference on Modeling and Simulation, 2003.
  • 16
    • 34447521332 scopus 로고    scopus 로고
    • R.R. Lbatullin, N.G. Lbragimov, R.S. Khisamov, E.D. Podymov, A.A. Shutov, Application and method based on artificial intelligence for selection of structures and screening of technologies for enhanced oil recovery, SPE 75175, in: Proc. SPE/DOE Improved Oil Recovery Symposium, Tulsa, Oklahoma, 2002.
  • 17
    • 34447516610 scopus 로고    scopus 로고
    • Y. Liu, B. Bai, Y.X. Li, J.-P. Coste, Optimization design for conformance control based on profile modification treatments of multiple injectors in a reservoir, SPE 64731, in: Proc. the 2000 SPE Symposium, Beijing, 2000.
  • 18
    • 1542345396 scopus 로고    scopus 로고
    • W. Liu, C. Xiao, B. Wang, Y. Shi, S. Fang, Study on combining subtractive clustering with fuzzy c-means clustering, in: Proc. the 2nd International Conference on Machine Learning and Cybernetics, Xi'an, China, 2003, pp. 2659-2662.
  • 19
  • 20
    • 13244268569 scopus 로고    scopus 로고
    • Intelligent control of a stepping motor drive using an adaptive neuro-fuzzy inference system
    • Melin P., and Castillo O. Intelligent control of a stepping motor drive using an adaptive neuro-fuzzy inference system. Information Sciences 170 2-4 (2005) 133-150
    • (2005) Information Sciences , vol.170 , Issue.2-4 , pp. 133-150
    • Melin, P.1    Castillo, O.2
  • 21
    • 0035416271 scopus 로고    scopus 로고
    • The shape of fuzzy sets in adaptive function approximation
    • Mitaim S., and Kosko B. The shape of fuzzy sets in adaptive function approximation. IEEE Transactions on Fuzzy Systems 9 4 (2001) 637-656
    • (2001) IEEE Transactions on Fuzzy Systems , vol.9 , Issue.4 , pp. 637-656
    • Mitaim, S.1    Kosko, B.2
  • 22
    • 34447509121 scopus 로고    scopus 로고
    • M.M. Reda Taha, A. Noureldin, N. El-Sheimy, Improving INS/GPS positioning accuracy during GPS outages using fuzzy logic, in: Proc. GPS-GNSS 2003, Oregon, 2003, pp. 499-508.
  • 23
    • 0031988304 scopus 로고    scopus 로고
    • The impact of poor data on the typical enterprise
    • Redman T.C. The impact of poor data on the typical enterprise. Communications of the ACM (1998) 79-82
    • (1998) Communications of the ACM , pp. 79-82
    • Redman, T.C.1
  • 24
    • 21844460630 scopus 로고    scopus 로고
    • Data errors in neural network and linear regression models: an experimental comparison
    • Rossin D.F., and Klein B.D. Data errors in neural network and linear regression models: an experimental comparison. Data Quality 5 1 (1999) 33-43
    • (1999) Data Quality , vol.5 , Issue.1 , pp. 33-43
    • Rossin, D.F.1    Klein, B.D.2
  • 26
    • 0021314119 scopus 로고    scopus 로고
    • T. Takagi, M. Sugeno. Derivation of fuzzy control rules from human operator's control actions. In: Proc. the IFAC Symp. on Fuzzy Information, Knowledge Representation and Decision Analysis, 1983, pp. 55-60.
  • 27
    • 3042859057 scopus 로고    scopus 로고
    • D. Tamhane, P.M. Wong, F. Aminzadeh, M. Nikravesh, Soft computing for intelligent reservoir characterization, SPE 59397, in: Proc. SPE Asia Pacific Conference on Integrated Modeling for Asset Management, Yokohama, Japan, 2000.
  • 28
    • 85085408232 scopus 로고    scopus 로고
    • J. Wang, X. Li, H. Li, Prediction of injection profile of an injector using a fuzzy mathematical method, CIPC2005-134, in: Proc. Petroleum Society's 6th Canadian International Petroleum Conference (56th Annual Technical Meeting), Calgary, Alberta, Canada, 2005.
  • 29
    • 1642558162 scopus 로고    scopus 로고
    • W. Weiss, R. Balch, How artificial intelligence methods can forecast oil production, SPE 75143, in: Proc. SPE/DOE Improved Oil recovery Symposium, Tulsa, Oklahoma, 2002.
  • 30
  • 32
    • 18144388681 scopus 로고    scopus 로고
    • Toward a generalized theory of uncertainty (GTU) - an outline
    • Zadeh L.A. Toward a generalized theory of uncertainty (GTU) - an outline. Information Sciences 172 (2005) 1-40
    • (2005) Information Sciences , vol.172 , pp. 1-40
    • Zadeh, L.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.