Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques

Applied Intelligence

Volumn 10, Issue 1, 1999, Pages 5-24

  Cordón, Oscar ^a   Herrera, Francisco ^a   Sánchez, Luciano ^b,c  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF OVIEDO   (Spain)

^c Esc Tenica Sup Ingenieros I   (Spain)

Author keywords

Data analysis; Electrical engineering; Evolutionary algorithms; Genetic algorithm program; Genetic fuzzy rule based systems

Indexed keywords

DATA REDUCTION; FUZZY SETS; GENETIC ALGORITHMS; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; STATISTICAL METHODS;

EVOLUTIONARY ALGORITHMS; GENETIC FUZZY RULE BASED SYSTEMS; GENETIC PROGRAMMING;

ELECTRIC POWER DISTRIBUTION;

EID: 0032674647     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008384630089     Document Type: Article

References (42)

1. O. Cordón, F. Herrera, and L. Sánchez, "Computing the Spanish medium electrical line maintenance costs by means of evolution-based learning processes," in Proceedings of the Eleventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA-98-AIE), Castellón, vol. 1, pp. 478-482, 1998.
2. L. Sánchez, "Estudio de la red asturiana de baja tensión rural y urbana," Technical Report, Hidroeléctrica del Cantábrico Research and Development Department (in Spanish), Asturias, Spain, 1997.
3. T. Bäck, Evolutionary Algorithms in Theory and Practice, Oxford University Press, 1996.
4. L. Howard and D. D'Angelo, "The GA-P: A genetic algorithm and genetic programming hybrid," IEEE Expert, pp. 11-15, 1995.
5. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
6. H.P. Schwefel, Evolution and Optimum Seeking. Sixth-Generation Computer Technology Series, John Wiley and Sons, 1995.
7. A. Bardossy and L. Duckstein, Fuzzy Rule-Based Modeling With Application to Geophysical, Biological and Engineering Systems, CRC Press, 1995.
8. D. Driankov, H. Hellendoorn, and M. Reinfrank, An Introduction to Fuzzy Control, Springer-Verlag, 1993.
9. T. Takagi and M. Sugeno, "Fuzzy identification of systems and its application to modeling and control," IEEE Transactions on Systems, Man, and Cybernetics, vol. 15, no. 1, pp. 116-132, 1985.
10. O. Cordón and F. Herrera, "A general study on genetic fuzzy systems," in Genetic Algorithms in Engineering and Computer Science, edited by J. Periaux, G. Winter, M. Galán, and P. Cuesta, John Wiley and Sons, pp. 33-57, 1995.
11. A.K. Jain and R.C. Dubes, Algorithmsfor Clustering Data, Prentice Hall, 1988.
12. S. Chatterjee and B. Price, Regression Analysis by Examples, John Wiley and Sons, 1991.
13. P.D. Wasswerman, Advanced Methods in Neural Computing, Van Nostrand Reinhold, 1993.
14. J.J. Grefensette (Ed.), Genetic Algorithms for Machine Learning, Kluwer Academic Press, 1994.
15. E. Vonk, L.C. Jain, and R.P. Johnson, Automatic Generation of Neural Network Architecture Using Evolutionary Computation, World Scientific, 1997.
16. J. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection. The MIT Press, 1992.
17. F. Herrera and J.L. Verdegay (Eds.), Genetic Algorithms and Soft Computing, Physica-Verlag, 1996.
18. L.A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338-353, 1965.
19. W. Pedrycz (Ed.), Fuzzy Modelling: Paradigms and Practice, Kluwer Academic Press, 1996.
20. L.X. Wang, Adaptive Fuzzy Systems and Control, Prentice-Hall, 1994.
21. R.R. Yager and L.A. Zadeh (Eds.), An Introduction to Fuzzy Logic Applications in Intelligent Systems, Kluwer Academic Press, 1992.
22. P.P. Bonissone, "Soft computing: The convergence of emerging reasoning technologies," Soft Computing, vol. 1, no. 1, pp. 6-18, 1997.
23. O. Cordón, F. Herrera, and M. Lozano, "A classified review on the combination fuzzy logic-genetic algorithms bibliography: 1989-1995," in Genetic Algorithms and Fuzzy Logic Systems. Soft Computing Perspectives, edited by E. Sanchez, T. Shibata, and L. Zadeh, World Scientific, pp. 209-241, 1997.
24. O. Cordón, F. Herrera, and M. Lozano, "On the combination of fuzzy logic and evolutionary computation: A short review and bibliography," in Fuzzy Evolutionary Computation, edited by W. Pedrycz, Kluwer Academic Press, pp. 57-77, 1997.
25. O. Cordón and F. Herrera, "A three-stage evolutionary process for learning descriptive and approximative fuzzy logic controller knowledge bases from examples," International Journal of Approximate Reasoning, vol. 17, no. 4, pp. 369-407, 1997.
26. L. Sánchez, "Interval-valued GA-P Algorithms," Technical Report, Dept. of Computer Science, University of Oviedo, Oviedo, Spain, 1997.
27. L.X. Wang and J.M. Mendel, "Generating fuzzy rules by learning from examples," IEEE Transactions on Systems, Man, and Cybernetics, vol. 22, no. 6, pp. 1414-1427, 1992.
28. O. Cordón and F. Herrera, "A three-stage method for designing genetic fuzzy systems by learning from examples," in Proceedings of the Fourth International Conference on Parallel Problem Solving from Nature, PPSN IV, L.N.C.S. 1141, edited by H.M. Voight, W. Ebeling, E. Rechemberg, and H.P. Schwefel, Springer-Verlag: Berlin, 1996, pp. 720-729.
29. J.E. Baker, "Reducing bias and inefficiency in the selection algorithm," in Proceedings of the Second International Conference on Genetic Algorithms (ICGA'87), Hillsdale, 1987, pp. 14-21.
30. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, 1996.
31. F. Herrera, M. Lozano, and J.L. Verdegay, "Tuning fuzzy controllers by genetic algorithms," International Journal of Approximate Reasoning, vol. 12, pp. 299-315, 1995.
32. F. Herrera, M. Lozano, and J.L. Verdegay, "Fuzzy connectives based crossover operators to model genetic algorithms population diversity," Fuzzy Sets and Systems, vol. 92, no. 1, pp. 21-30, 1997.
33. A. González and R. Pérez, "Completeness and consistency conditions for learning fuzzy rules," Fuzzy Sets and Systems, vol. 96, no. 1, pp. 37-51, 1998.
34. O. Cordón and F. Herrera, "A two-stage evolutionary process for designing TSK fuzzy rule-based systems," Technical Report DECSAI-97115, Dept. of Computer Science and A.I, University of Granada, Spain, 1997.
35. P. Jog, J.Y. Suh, and D.V. Gutch, "The effects of population size, heuristic crossover and local improvement on a genetic algorithm," in Proceedings of the Third International Conference on Genetic Algorithms (ICGA), pp. 110-115, 1989.
36. J.Y. Suh and D.V. Gutch, "Incorporating heuristic information on genetic search," in Proceedings of the Second International Conference on Genetic Algorithms (ICGA), 1987, pp. 100-107.
37. O. Cordón and F. Herrera, "Evolutionary design of TSK fuzzy rule-based systems using (μ, λ)-evolution strategies," in Proceedings of the Sixth IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'97), Barcelona, 1997, vol. 1, pp. 509-514.
38. F. Herrera, M. Lozano, and J.L. Verdegay, "A learning process for fuzzy control rules using genetic algorithms," Fuzzy Sets and Systems, 1998, to appear.
39. K. Deb and D.E. Goldberg, "An investigation of niche and species formation in genetic function optimization," in Proceedings of the Second International Conference on Genetic Algorithms (ICGA), Hillsdale, 1989, pp. 42-50.
40. J. Koza and J. Rice, Genetic Programming, The MIT Press, 1994.
41. G. Bojadziev, Fuzzy Sets, Fuzzy Logic, Applications, World Scientific, 1995.
42. H. Ishibuchi, H. Tanaka, and H. Okada, "An architecture of neural networks with interval weights and its application to fuzzy regression analysis," Fuzzy Sets and Systems, vol. 57, pp. 27-39, 1993.