Neural network construction and training using grammatical evolution

Neurocomputing

Volumn 72, Issue 1-3, 2008, Pages 269-277

  Tsoulos, Ioannis ^a   Gavrilis, Dimitris ^b   Glavas, Euripidis ^c  

^a UNIVERSITY OF IOANNINA   (Greece)

^b UNIVERSITY OF PATRAS   (Greece)

^c Epirus Institute of Technology Arta   (Greece)

Author keywords

Context free grammar; Genetic algorithm; Grammatical evolution; Neural network

Indexed keywords

COMPETITION; COMPUTATIONAL GRAMMARS; ELECTRIC NETWORK TOPOLOGY; GENETIC ALGORITHMS; IMAGE CLASSIFICATION; TOPOLOGY;

CONTEXT-FREE GRAMMAR; CONVENTIONAL ALGORITHMS; DATA SETS; FORMAL GRAMMARS; GRAMMATICAL EVOLUTION; GRAMMATICAL EVOLUTIONS; NETWORK ARCHITECTS; NETWORK CONSTRUCTIONS; NETWORK EVOLUTIONS; NETWORK PARAMETERS; NETWORK TOPOLOGIES; NEURAL NETWORK TRAININGS; REGRESSION PROBLEMS; SEARCH SPACES;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHROMOSOME ANALYSIS; CLASSIFICATION; GENETIC ALGORITHM; GRAMMAR; METHODOLOGY; MOLECULAR EVOLUTION; PATTERN RECOGNITION; PHENOTYPE; PRIORITY JOURNAL; REGRESSION ANALYSIS; SIMULATION;

EID: 55949107365     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.01.017     Document Type: Article

References (38)

1. Abbass H.A. An evolutionary artificial neural networks approach for breast cancer diagnosis. Artif. Intell. Med. 25 3 (July 2002) 265-281
2. Abraham A. Meta learning evolutionary artificial neural networks. Neurocomputing 56 (2004) 1-38
3. Bishop C. Neural Networks for Pattern Recognition (1995), Oxford University Press, Oxford
4. Brabazon A., and O'Neill M. In: Arabnia H.R. (Ed). Proceedings of the International Conference on Artificial Intelligence vol. II (2003), CSREA Press 492-498
5. Broyden C.G. The convergence of a class of double-rank minimization algorithms: Part I and II. J. Inst. Math. Appl. 6 (1970) 76-90
6. Carlos J., Pujol F., and Poli R. Evolution of the topology and the weights of neural networks using genetic programming with a dual representation. Appl. Intell. 8 (1998) 73-84
7. J.J. Collins, C. Ryan, in: Proceedings of AROB 2000, Fifth International Symposium on Artificial Life and Robotics, 2000.
8. Cybenko G. Approximation by superpositions of a sigmoidal function. Math. Control Signals Systems 2 (1989) 303-314
9. M.C.P. de Souto, A. Yamazaki, T.B. Ludernir, Optimization of neural network weights and architecture for odor recognition using simulated annealing, in: Proceedings of the 2002 International Joint Conference on Neural Networks, vol. 1, 2002, pp. 547-552.
10. Dieferson L.A. Araujo, Heitor S. Lopes, Alex A. Freitas, A parallel genetic algorithm for rule discovery in large databases, in: Proceedings of the IEEE Systems, Man and Cybernetics Conference, vol. III, Tokyo, Japan, 12-15 October 1999, pp. 940-945.
11. Fletcher R.E. A new approach to variable metric algorithms. Comput. J. 13 (1970) 317-322
12. Gao W. Study on new evolutionary neural network. Int. Conf. Mach. Learn. Cybernet. 2 (Nov 2003) 1287-1292
13. D. Gavrilis, I. Tsoulos, G. Georgoulas, E. Glavas, Classification of fetal heart rate using grammatical evolution, in: IEEE 2005 Workshop on Signal Processing Systems.
14. Han S.-J., and Cho S.-B. Evolutionary neural networks for anomaly detection based on the behavior of a program. IEEE Trans. Systems, Man Cybernet. 36 3 (2006)
15. Jung J.-Y., and Reggia J.A. Evolutionary design of neural network architectures using a descriptive encoding language. IEEE Trans. Evol. Comput. 10 6 (2006)
16. K.-J. Kim, S.-B. Cho, Evolving artificial neural networks for DNA microarray analysis, in: The 2003 Congress on Evolutionary Computation (CEC '03), vol. 4, December 2003, pp. 2370-2377.
17. Kim K.-J., and Cho S.-B. Evolved neural networks based on cellular automata for sensory-motor controller. Neurocomputing 69 (2006) 2193-2207
18. J.R. Koza, J.P. Rice, Genetic generation of both the weights and architecture for a neural network, in: International Joint Conference on Neural Networks, IJCNN-91, II: pp. 397-404, 8-12, 1991.
19. Lagaris I.E., Likas A., and Fotiadis D.I. Artificial neural networks for solving ordinary and partial differential equations. IEEE Trans. Neural Networks 9 (1998) 987-1000
20. Z. Michalewicz, Genetic Algorithms+Data Structures=Evolution Programs, third ed., Springer, Berlin.
21. O'Neill M., and Ryan C. In: Miettinen K., Mkel M.M., Neittaanmki P., and Periaux J. (Eds). Evolutionary Algorithms in Engineering and Computer Science (1999), Jyvskyl, Finland 127-134
22. O'Neill M., and Ryan C. Grammatical evolution. IEEE Trans. Evol. Comput. 5 (2001) 349-358
23. O'Neill M., and Ryan C. Grammatical Evolution: Evolutionary Automatic Programming in a Arbitary Language, Genetic Programming vol. 4 (2003), Kluwer Academic Publishers, Dordrecht
24. R. Poli, Discovery of symbolic, neuro-symbolic and neural networks with parallel distributed genetic programming. In: G.D. Smith, N.C. Steele, R.F. Albrecht (Eds.), Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference, ICANNGA97, University of East Anglia, Norwich, UK, 1997. Springer, Berlin, 1998.
25. Powell M.J.D. A tolerant algorithm for linearly constrained optimization calculations. Mathematical Programming 45 (1989)
26. Reed R. Pruning algorithms-a survey. IEEE Trans. Neural Networks 4 (1993) 740-747
27. M. Riedmiller, H. Braun, A direct adaptive method for faster backpropagation learning: the {RPROP} algorithm, in: Proceedings of the {IEEE} International Conference on Neural Networks, 1993, pp. 586-591.
28. Rivas V.M., Merelo J.J., Castillo P.A., Arenas M.G., and Castellano J.G. Evolving RBF neural networks for time-series forecasting with EvRBF. Inform. Sci. 165 3-4 (19 Oct 2004) 207-220
29. C. Ryan, M. O'Neill, J.J. Collins, in: Proceedings of Mendel 1998: Fourth International Mendel Conference on Genetic Algorithms, Optimization Problems, Fuzzy Logic, Neural Networks, Rough Sets, Brno, Czech Republic, Technical University of Brno, Faculty of Mechanical Engineering, 1998, pp. 111-119.
30. Sin Man Cheang, Kin Hong Lee, Kwong Sak Leung, Data classification using genetic parallel programming, in: E. Cant'u-Paz, J.A. Foster, K. Deb, D. Davis, R. Roy, U.-M. O'Reilly, H.-G. Beyer, R. Standish, G. Kendall, S. Wilson, M. Harman, J. Wegener, D. Dasgupta, M.A. Potter, A.C. Schultz, K. Dowsland, N. Jonoska, J. Miller (Eds.), Genetic and Evolutionary Computation-GECCO-2003, vol. 2724 of Lecture Notes in Computer Science, Chicago, 12-16 July 2003, Springer, Berlin, pp. 1918-1919.
31. Sin Man Cheang, Kin Hong Lee, Kwong Sak Leung, Evolving data classification programs using genetic parallel programming, in: Ruhul Sarker, Robert Reynolds, Hussein Abbass, Kay Chen Tan, Bob McKay, Daryl Essam, Tom Gedeon (Eds.), Proceedings of the 2003 Congress on Evolutionary Computation CEC2003, Canberra, 8-12 December 2003, IEEE Press, New York, pp.248-255.
32. C. Sung-Bae, K. Shimohara, Modular neural networks evolved by genetic programming, in: Proceedings of the IEEE International Conference on Evolutionary Computation, 20-22 May 1996, pp. 681-684.
33. Sven E. Eklund, Time series forecasting using massively parallel genetic programming, in: Proceedings of Parallel and Distributed Processing International Symposium, 22-26 April 2003, pp. 143-147.
34. I. Tsoulos, G. Georgoulas, D. Gavrilis, C. Stylios, Introducing Grammatical Evolution for FHR analysis and classification, in: Third IEEE Conference on Intelligent Systems.
35. Tsoulos I.G., and Lagaris I.E. MinFinder: locating all the local minima of a function. Comput. Phys. Commun. 174 2 (January 2006) 166-179
36. L. Wang, G. Yu, G. Wang, D. Wang, Method of evolutionary neural network-based intrusion detection, in: International Conferences on Info-tech and Info-net 2001 (ICII 2001), vol. 5, Oct.-Nov. 2001, pp. 13-18.
37. Yao X. Evolving artificial neural networks. Proc. IEEE 87 9 (1999) 1423-1447
38. Zhang C., Shao H., and Li Y. Particle swarm optimization for evolving artificial neural networks. IEEE Int. Conf. Systems, Man Cybergenet. (2000) 2487-2490