A data mining based genetic algorithm

Proc. - The Fourth IEEE Workshop on Software Technol. for Future Embedded and Ubiquitous Syst., SEUS 2006 andthe Second Int. Workshop on Collaborative Comput., Integr., and Assur., WCCIA 2006

Volumn 2006, Issue , 2006, Pages 55-60

  Wu, Yi Ta ^a   An, Yoo Jung ^b   Geller, James ^b   Wu, Yih Tyng ^c  

^a UNIVERSITY OF MICHIGAN   (United States)

^b New Jersey Institute of Technology   (United States)

^c NOVA SOUTHEASTERN UNIVERSITY   (United States)

Author keywords

Data mining; Digital watermarking; Evolutionary algorithm; Genetic algorithm

Indexed keywords

DNA EXTRACTION; EVOLUTIONARY ITERATIONS; GENETIC COMBINATIONS;

DATA MINING; DIGITAL WATERMARKING; DNA; EVOLUTIONARY ALGORITHMS;

GENETIC ALGORITHMS;

EID: 33750905521     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SEUS-WCCIA.2006.2     Document Type: Conference Paper

References (14)

1. J. H. Holland, Adaptation in Natural and Artificial Systems, The University of Michigan Press, 1975.
2. Y.-T. Wu and F. Y. Shih, "An adjusted-purpose digital watermarking technique," Pattern Recognition, vol. 37, no. 12, pp. 2349-2359, Dec. 2004.
3. F. Y. Shih and Y.-T. Wu, "Decomposition of binary morphological structuring elements based on genetic algorithms," Computer Vision and Image Understanding, vol. 99, no. 2, pp. 291-302, August 2005
4. Y.-T. Wu and F. Y. Shih, "Genetic Algorithm Based Methodology for Breaking the Steganalytic Systems," IEEE Trans. on Systems, Man and Cybernetics, Part B, vol. 36, no. 1, pp. 24-31, Feb. 2006.
5. F. Y. Shih and Y.-T. Wu, "Enhancement of image watermark retrieval based on genetic algorithm," Journal of Visual Communication and Image Representation, vol. 16, pp. 115-133, April 2005.
6. N. Melab and E. Talbi, "A parallel genetic algorithm for rule mining," Proc. of the 15th International Parallel & Distributed Processing Symposium, pp.1347-1352, San Francisco, CA, USA, 2001.
7. W. Pedrycz, Z. A. Sosnowski, "Genetically optimized fuzzy decision trees," IEEE Trans. on Systems, Man and Cybernetics, Part B, vol. 35, no. 3, pp. 633-641, June 2005.
8. K. Namjin, N. Kehtarnavaz, M. B. Yeary, S. Thornton, "DSP-based hierarchical neural network modulation signal classification," IEEE Trans. on Neural Networks, vol. 14, no. 5, pp. 1065-1071, Sep. 2003.
9. S. G. Mougiakakou, I. Valavanis, K. S. Nikita, A. Nikita, and D. Kelekis, "Characterization of CT liver lesions based on texture features and a multiple neural network classification scheme," Proc. of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2, pp. 17-21, Cancun , Mexico, Sep. 2003.
10. D. T. Larose, Discovering Knowledge in Data: An Introduction to Data Mining, Wiley Publishers, 2004.
11. U. Fayyad, "Data mining and knowledge discovery in databases: implications for scientific database," Proc. of the 9th International Conference on Scientific and Statistical Database Management, pp. 2-11, 1997.
12. C. Apte, B. Liu, E. P. D. Pednault, and P. Smyth, "Business applications of data mining," Communications of the ACM, vol. 45, no. 8, pp. 49-53, 2002.
13. M. Garofalakis, R. Rastogi, and K. Shim, "Mining sequential patterns with regular expression constraints," IEEE Trans. on Knowledge and Data Engineering, vol. 14, no. 3, pp. 530-552, 2002.
14. X. Chen, X. Zhou, R. B. Scherl and J. Geller, "Using an interest ontology for improved support in rule mining," Proc. of the 5th International Conference Data Warehousing and Knowledge Discovery, pp. 320-329, Prague, Czech Republic, Sep. 2003.