AN EMPIRICAL STUDY OF NON-BINARY GENETIC ALGORITHM-BASED NEURAL APPROACHES FOR CLASSIFICATION

Proceedings of the 20th International Conference on Information Systems, ICIS 1999

Volumn , Issue , 1999, Pages 155-165

  Pendharkar, Parag C ^a   Rodger, James A ^b  

^a Pennsylvania State University at Harrisburg   (United States)

^b INDIANA UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

discriminant analysis; genetic algorithms; Neural networks

Indexed keywords

DISCRIMINANT ANALYSIS; GENETIC ALGORITHMS; INFORMATION SYSTEMS; INFORMATION USE; LEARNING ALGORITHMS;

BACK-PROPAGATION ALGORITHM; BINARY GENETIC ALGORITHM; CONNECTION WEIGHTS; EMPIRICAL STUDIES; HIGH RELIABILITY; NEURAL-NETWORKS; NON-BINARY; OVERFITTING; SIMULATED DATASETS; TRAINING DATASET;

NEURAL NETWORKS;

EID: 85032266822     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Abad, P. L., and Banks, W. J. “New LP Based Heuristics for the Classification Problem,” European Journal of Operations Research (67), 1993, pp. 88-100.
2. Banks, W. J., and Abad, P. L “An Efficient Optimal Solution for the Classification Problem,” Decision Sciences (22:5), 1991, pp. 1008-1023.
3. Bhattacharyya, S., and Pendharkar P. C. “Inductive Evolutionary and Neural Techniques for Discrimination,” Decision Sciences (29:4), 1998, pp. 871-899.
4. Curry, B., and Morgan, P. “Neural Networks: A Need for Caution,” Omega: The International Journal of Management Science (25:1), February 1997, pp. 123-133.
5. Goldberg, D. Genetic Algorithms in Search, Optimization, and Machine Learning, Reading, MA: Addison Wesley Longman, Inc., 1989.
6. Goldberg, D. E., and Deb, K. “A Comparative Analysis of Selection Schemes Used in Genetic Algorithms,” in Foundations of Genetic Algorithms, G. Rawlins (ed.), San Mateo, CA: Morgan Kaufmann, 1991, pp. 69-93.
7. Hung, M. S., and Denton, J. A. “Training Neural Networks with GRG2 Nonlinear Optimizer,” European Journal of Operational Research (69), 1993, pp. 83-91.
8. Janikow, C. Z., and Michalewicz, Z. “An Experimental Comparison of Binary and Floating Point Representations in Genetic Algorithms,” in Fourth International Conference on Genetic Algorithms, 1991, pp. 31-36.
9. Joachimsthaler, E. A., and Stam, A. “Four Approaches to the Classification Problem in Discriminant Analysis: An Experimental Study,” Decision Sciences (19), 1988, pp. 322-333.
10. Koehler, G. J. “Linear Discriminant Functions Determined by Genetic Search,” ORSA Journal on Computing (3:4), Fall 1991, pp. 345-357.
11. Koehler, G. J., and Erenguc, S. S. “Minimizing Misclassifications in Linear Discriminant Analysis,” Decision Sciences (21), 1990, pp. 63-85.
12. Miller, G. F.; Todd, P. M.; and Hedge, S. U. “Designing Neural Networks using Genetic Algorithms,” in Proceedings of Second International Conference of Genetic Algorithms, 1989, pp. 379-383.
13. Moriarty, D. E., and Miikkulainen, R. “Forming Neural Networks Through Efficient and Adaptive Coevolution,” Evolutionary Computation (5:4), 1998, pp. 373-399.
14. Pendharkar, P. C. “Neural Approaches in Noisy and Kurtotic Environments,” under review, 1999 (available from the first author).
15. Pendharkar, P. C., and Rodger, J. A. “A Non-Linear Programming and Genetic Search Application for Production Scheduling in Coal Mines,” Annals of Operations Research, forthcoming, 2000.
16. Rooij, A. J. F.; Jain, L. C.; and Johnson, R. P. Neural Network Training Using Genetic Algorithms” Series in Machine Perception and Artificial Intelligence, Volume 26, Singapore: World Scientific Publishers, 1998.
17. Salomon, R. “Evolutionary Algorithms and Gradient Search: Similarities and Differences,” IEEE Transactions on Evolutionary Computation (2:2), 1998, pp. 45-55.
18. Sexton, R. S.; Alidaee, B.; Dorsey, R. E.; and Johnson, J. D. “Global Optimization for Artificial Neural Networks: A Tabu Search Application,” European Journal of Operational Research (106), 1998, pp. 570-584.
19. Sexton, R. S.; Dorsey, R. E.; and Johnson, J. D. “Optimization of Neural Networks: A Comparative Analysis of the Genetic Algorithm and Simulated Annealing,” European Journal of Operational Research (114), 1999, pp. 589-601.
20. Syswerda, G. “Uniform Crossover in Genetic Algorithms,” in Proceedings of Third International Conference on Genetic Algorithms, 1990, pp. 2-9.
21. Whitley, D., and Hanson, T. “Optimizing Neural Networks Using Faster, More Accurate Genetic Search,” Proceedings of Second International Conference on Genetic Algorithms, 1989, pp. 391-396.
22. Wilson, S. W. “GA: Easy Does Not Imply Steepest-Ascent Optimizable,” in Proceedings of Fourth International Conference on Genetic Algorithms, 1991, pp. 85-89.
23. Yanev, N., and Balev, S. “A Combinatorial Approach to the Classification Problem,” European Journal of Operational Research (115), 1999, pp. 339-350.