Design of ANFIS networks using hybrid genetic and SVD methods for the modelling of explosive cutting process

Journal of Materials Processing Technology

Volumn 155-156, Issue 1-3, 2004, Pages 1415-1421

  Nariman Zadeh, N ^a   Darvizeh, A ^a   Dadfarmai, M H ^a  

^a UNIVERSITY OF GUILAN   (Iran)

Author keywords

ANFIS; Explosive cutting process; Genetic algorithms; SVD

Indexed keywords

FUZZY CONTROL; GENETIC ALGORITHMS; HEURISTIC METHODS; LARGE SCALE SYSTEMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; CUTTING TOOLS; SHAPED CHARGES;

ANFIS MODELS; ANFIS NETWORKS; LINEAR COEFFICIENTS; SINGULAR VALUE DECOMPOSITION (SVD);

IDENTIFICATION (CONTROL SYSTEMS); SINGULAR VALUE DECOMPOSITION;

ANFIS; ANFIS MODEL; APEX ANGLES; CUTTING PROCESS; GAUSSIAN MEMBERSHIP FUNCTION; HYBRID GENETIC; LINEAR COEFFICIENTS; LINER THICKNESS; OPTIMAL DESIGN; SVD METHOD;

EID: 10044263081     PISSN: 09240136     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmatprotec.2004.04.228     Document Type: Article

References (30)

1. K.J. Astrom, P. Eykhoff, System identification, a survey, Automatica 7 (1971) 123-162.
2. E. Sanchez, T. Shibata, L.A. Zadeh, Genetic Algorithms and Fuzzy Logic Systems, World Scientific, 1997.
3. K. Kristinson, G. Dumont, System identification and control using genetic algorithms, IEEE Trans. Syst. Man Cybern. 22 (5) (1992) 1033-1046.
4. J. Koza, Genetic Programming, on the Programming of Computers by Means of Natural Selection, MIT Press, 1992.
5. H. Iba, T. Kuita, H. de Garis, T. Sator, System identification using structured genetic algorithms, in: Proceedings of 5th International Conference on Genetic Algorithms, ICGA'93, USA, 1993.
6. B. Porter, N. Nariman-Zadeh, Genetic design of computed-torque controllers for robotic manipulators, in: IASTED International Conference on Sys. and Cont., Switzerland, 1994.
7. C.C. Lee, Fuzzy logic in control systems: fuzzy logic controller, IEEE Trans. Syst. Man Cybern. 20 (2) (1990) 404-434.
8. L.X. Wang, Fuzzy systems are universal approximators, in: Proceedings of IEEE International Conference on Fuzzy Systems, USA, 1992, pp. 1163-1170.
9. X.J. Zeng, M.G. Singh, Approximation theory for fuzzy systems - SISO case, IEEE Trans. Fuzzy Syst. 20 (2) (1994) 162-176.
10. B. Kosko, Fuzzy systems as universal approximator, IEEE Trans. Computers 43 (11) (1994) 1329-1333.
11. C.L. Karr, Applying genetics to fuzzy logic, AI Expert 6 (1991) 38-13.
12. B. Porter, N. Nariman-Zadeh, Genetic design of computed-torque/fuzzy- logic controllers for robotic manipulators, in: Proc. IEEE Int. Symp. on Int. Control, USA, 1995.
13. B. Porter, N. Nariman-Zadeh, Evolutionary design of fuzzy-logic controllers for manufacturing systems, Ann. CIRP 46/1 (1997) 425-428.
14. O. Cordon, F. Herrera, F. Hoffmann, L. Magdalena, Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases, Advances in Fuzzy Systems, World Scientific, Singapore, 2001.
15. L. Wang, R. Langari, J. Yen, Identifying fuzzy rule-based models using orthogonal transformation and back propagation, in: C.T. Leondes (Ed.), Fuzzy Theory Systems: Techniques and Application, vol. 1, Academic Press, 1999.
16. N. Nariman-Zadeh, A. Darvizeh, Design of fuzzy systems for the modelling of explosive cutting process of plates using singular value decomposition, in: WSES 2001 Conference on Fuzzy Sets and Fuzzy Systems (FSFS'0l), Spain, 2001.
17. A. Darvizeh, N. Nariman-Zadeh, H. Gharababei, GMDH-Type Neural Network Modelling of Explosive Cutting Process of Plates Using Singular Value Decomposition, ESM'2001, Prague, 2001.
18. N. Nariman-zadeh, A. Darvizeh, F. Oliaei, Genetic algorithm and singular value decomposition in the design of fuzzy systems for the modelling of explosive cutting process, in: WSES Conference on Fuzzy Sets and Fuzzy Systems FSFS'02, Switzerland, 2002.
19. M. Sugeno, G.T. Kang, Structure identification of fuzzy model, Fuzzy Sets and Systems 28 (1988) 15-33.
20. T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modelling and control, IEEE Trans. Syst. Man Cybern. 15 (1985) 116-132.
21. M. Mannle, FTSM-Fast Takagi-Sugeno Fuzzy Modelling, Institute for Computer Design and Fault Tolerance, University of Karlsruhe, Germany, 2001.
22. M.R. Delgado, F. Von Zuben, F. Gomide, Hierarchical genetic fuzzy systems, Inf. Sci. 136 (2001) 29-52.
23. J.-S.R. Jang, ANFIS: adaptive-network-based fuzzy inference system, IEEE Trans. Syst. Man Cybern. 23 (1993) 665-685.
24. J.-S.R. Jang, C.-T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computation Approach to Learning and Machine Intelligence, Prentice Hall, 1997.
25. A. Rizzi, F.M.F. Mascioli, G. Martinelli, Automatic training of ANFIS networks, in: Proceedings of IEEE International Fuzzy Systems Conference, Korea, 1999.
26. S.A. Salem, S.T.S. Al-Hassani, Penetration by high speed oblique jets: theory and experiments, Int. J. Mech. Sci. 25 (12) (1983) 871-886.
27. M. Cheezari, Explosive Separation Using Shaped Charges, M.Sc. Dissertation (in Persian), Guilan University, Rasht, Iran, 1999.
28. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
29. G.H. Golub, C. Reinsch, Singular value decomposition and least squares solutions, Numer. Math. 14 (5) (1970) 403-20.
30. W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes: The Art of Scientific Computing, second ed., Cambridge University Press, 1992.