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Meta-BCS: a novel way to BCS ranking using generalized regression neural network and genetic algorithm

Published: 28 March 2008 Publication History

Abstract

In this paper, we attempt to run vulnerability analysis on the Bowl Championship Series (BCS) ranking system. We used Generalized Regression Neural Network (GRNN) to create a model for each poll and then applied these models to simulate a random season. After this, a modified genetic algorithm (GA) is applied to evolve schedules that minimize the difference between the number 2 ranked team and the number 3 ranked team. By simulating the seasons, we aim to show that current BCS system in fact converges faster than the proposed meta-BCS system.

References

[1]
Patterson, D. (1996). Artificial Neural Networks. Singapore, Prentice Hall.
[2]
Bishop, C. (1995). Neural Networks for Pattern Recognition. Oxford, University Press.
[3]
Russell, S. J. and Norvig, P. (1995) Artificial Intelligence: A Modern Approach, Prentice Hall.
[4]
Fogel, D. B.(2000). Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press.
[5]
Larranaga, P. and Lozano, J. A (2002). Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation, Kluwer Academic Publishers.
[6]
Dozier, G., Homaifar, A., Tunstel, E. and Battle, D., An Introduction to Evolutionary Computation
[7]
Zilouchian, A. & Jamshidi, M. (Eds.), Intelligent Control Systems Using Soft Computing Methodologies, CRC press
[8]
Holland, J., (1973) Genetic algorithms and the optimal allocations of trials, SIAM Journal of Computing, 2(2): 88--105.
[9]
Koza, J., (1993) Genetic Programming, MIT Press.
[10]
Holland, J., (1992) Adaptation in Natural and Artificial Systems, 2nd Ed., MIT Press.
[11]
Davis, L., (ed.), (1991) Handbook of Genetic Algorithms, Van Nostrand Reinhold New York.
[12]
Goldberg, D. E., (1989) Genetic Algorithms in Search, Optimization & Machine Learning. Addison-Wesley.
[13]
Lippmann, R. P., An introduction to computing with neural nets. IEE Assp. Mag. 4 (1987), pp. 4--22
[14]
Erb, R. J., Introduction to backpropagation neural network computation. Pharm. Res. 10 (1993), pp. 165--170
[15]
Speckt, D. F., A generalized regression neural network. IEEE Trans. Neural Networks 2 6 (1991), pp. 568--576.
[16]
Specht, D., A General Regression Neural Network. IEEE T. Neural Networks 1991, 2, 568--576.
[17]
Wasserman, P. D. (1993) Advanced Methods in Neural Computing, 155--161. Van Nostrand Reinhold, New York, USA.
[18]
http://www.eng.auburn.edu/~gvdozier/ACI
[19]
http://www.bcsfootball.org/bcsfootball/

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ACMSE '08: Proceedings of the 46th annual ACM Southeast Conference
March 2008
548 pages
ISBN:9781605581057
DOI:10.1145/1593105
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 March 2008

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Author Tags

  1. bowl championship series (BCS)
  2. generalized regression neural network (GRNN)
  3. genetic algorithm (GA)

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  • Research-article

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ACM SE08
ACM SE08: ACM Southeast Regional Conference
March 28 - 29, 2008
Alabama, Auburn

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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