Proposed a new method for rules extraction using artificial neural network and artificial immune system in cancer diagnosis

Journal of Bionanoscience

Volumn 7, Issue 6, 2013, Pages 665-672

  Javanmard, Reza ^a   JeddiSaravi, Kossar ^a   Alinejad Rokny, Hamid ^b,c  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

^c UNIVERSITY OF NEWCASTLE   (Australia)

Author keywords

ANN; Artificial immune system; Cancer diagnosis; Clustering; Learning; Rule extraction

Indexed keywords

EID: 84894242591     PISSN: 15577910     EISSN: 15577929     Source Type: Journal    
DOI: 10.1166/jbns.2013.1160     Document Type: Article

References (27)

1. R. Andrews, J. Diederich, and A. B. Tickle, Knowledge-Based Systems 8, 373 (1996).
2. G. Bologna, Journal of Applied Logic 2, 325 (2000).
3. C. J. Mantas, J. M. Puche, and J. M. Mantas, International Journal of Approximate Reasoning 43, 202 (2006).
4. S. H. Huang and H. Xing, Fuzzy Sets and Systems 132, 233 (2002).
5. A. B. Tickle, R. Andrews, M. Golea, and J. Diederich, Neural Networks Analysis: Architectures and Applications 61 (1997).
6. E. W. Saad and D. C. Wunsch, Neural Networks 20, 78 (2007).
7. E. Keedwell, A. Narayanan, and D. Savic, Evolving rules from neural networks trained on continuous data, Evolutionary computation, Proceedings of the 2000 Congress on Evolutionary Computation, La Jolla, CA (2000), Vol. 1, pp. 639-645.
8. S. I. Gallant, Communications of the ACM 31, 152 (1988).
9. G. G. Towell and J. Shavlik, Machine Learning 13, 71 (1993).
10. I. Sethi and J. Yoo, Engineering Intelligent Systems 4, 153 (1996).
11. H. Lu, R. Setiono, and H. Liu, IEEE Transactions on Knowledge and Data Engineering 8, 957 (1996).
12. R. Setiono and K. Leow, Applied Intelligence 12, 15 (2000).
13. V. Palade, D. Neagu, and G. Puscasu, Rule extraction from neural networks by interval propagation, Proceedings of the Fourth IEEE International Conference on Knowledge-Based Intelligent Engineering Systems Brighton, UK (2000), pp. 217-220.
14. A. S. D. Garcez, K. Broda, and D. M. Gabbay, Applied Intelligence 125, 155 (2001).
15. S. Snyders and C. Omlin, Rule extraction from knowledge-based neural networks with adaptive inductive bias, Proceedings of the Eighth International Conference on Neural Information Processing ICONIP (2001), Vol. 1, pp. 143-148.
16. Y. Jiang, Z. Zhou, and Z. Chen, Rule learning based on neural network ensemble, Proceedings of the International Joint Conference on Neural Networks Honolulu, HI (2002), pp. 1416-1420.
17. R. Setiono, W. K. Leow, and J. Zuarada, IEEE Transactions on Neural Networks 13, 564 (2002).
18. A. E. Elalfi, R. Haque, and M. E. Elalami, Applied Soft Computing 4, 65 (2004).
19. E. R. Hruschka and N. F. F. Ebecken, Neuro computing 70, 384 (2006).
20. S. L. Chiu, Journal of Intelligent and Fuzzy Systems-JIFS 2, 267 (1994).
21. R. P. Paiva and A. Dourado, Fuzzy Sets Syst. 147, 17 (2004).
22. R. K. Sivagaminathan and S. Ramakrishnan, Expert Systems with Applications, 33, 49 (2007).
23. L. N. De Castro and J. Timmis, Artificial immune systems, A New Computational Intelligence Approach, ISBN 978-1-85233-594-6, Springer, UK (2002).
24. T. Hou, C. Su, and H. Chang, Expert System with Applications 34, 427 (2008).
25. J. Timmis and C. A. Edmonds, Lecture notes in computer science, Springer 3102, 308 (2004).
26. R. De Attux, R. Duarte, L. T. Ferrari, R. Panazio, C. M. De Castro, L. N. Von Zuben, and J. M. Romano, MLP-based equalization and pre-distortion using an artificial immune network, Machine Learning for Signal Processing: IEEE Workshop (2005), pp. 177-182.
27. M. L. Repository, Http://www. ics. uci.edu/ mlearn/MLRepository. html: University of California, USA (1998).