Aggregation pheromone density based clustering

Proceedings - 9th International Conference on Information Technology, ICIT 2006

Volumn , Issue , 2006, Pages 259-264

  Kothari, Megha ^a   Ghosh, Susmita ^a   Ghosh, Ashish ^b  

^a JADAVPUR UNIVERSITY   (India)

^b INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

[No Author keywords available]

Indexed keywords

DATA STRUCTURES; INFORMATION MANAGEMENT; ONLINE SEARCHING;

CLUSTER VALIDITY;

CLUSTERING ALGORITHMS;

EID: 36049029954     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIT.2006.25     Document Type: Conference Paper

References (28)

1. G. H. Ball and D. J. Hall. ISODATA: A novel method of data analysis and pattern classification. Technical report, Stanford Research Institute, Menlo Park, CA, 1965.
2. W. J. Bell. Chemo-orientation in walking insects. In W. J. Bell and R. T. Carde, editors, Chemical Ecology of Insects, pages 93-109, 1984.
3. E. Bonabeau, M. Dorigo, and G. Theraulaz. Swarm Intelligence- From Natural to Artificial Systems. Santa Fe Institute in the Sciences of the Complexity, Oxford University Press, New York, 1999.
4. rd Intranational Conference on Machine Learning and Cybernetics, pages 1387-1392, Shanghai, August 2004.
5. st Conference on Simulation of Adaptive behavior: From Animals to Animats 1, pages 356-365. MIT press/Bradford Books, 1991.
6. M. Dorigo and L. M. Gambardella. Ant colony system: A cooperative learning apporach to the traveling salesman problem. IEEE TEC, 1(1):53-66, 1997.
7. M. Dorigo, V. Maniezzo, and A. Colorni. The ant system: Optimization by a colony of cooperating agents. IEEE Transaction on SMC-part B, 26(1):29-41, 1996.
8. M. Dorigo and T. Stützle. Ant Colony Optimization. Prentice Hall of India Private Limited, New Delhi, 2005.
9. A. P. Engelbrecht. Computational Intelligence:An Introduction. John Wiley and Sons, 2002.
10. nd International Conference on Knowledge Discovery and Data Mining, 1996.
11. M. Halkidi and M. Vazirgiannis. Clustering validity assessment: Finding the optimal partitioning of a data set. In Proceedings of ICDM, California, USA, 2001.
12. rd International Conference on Hybrid Intelligent Systems, Design and Application of Hybrid Intelligent Systems, pages 204-213. IOS press, 2003.
13. T. Kohonen. Self-Organizing Maps. Springer, Berlin, 1997.
14. rd International Conference on Machine Learning and Cybernetics, pages 1491-1496, Shanghai, August 2004.
15. E. D. Lumer and B. Faieta. Diversity and adaptation in populations of clustering ants. In D. Cliff, P. Husbands, J. A. Meyer, and S. W. Wilson, editors, Proceedings of the 3rd International Conference on Simulation of Adaptive Behaviour:From Animals to Animats 3, pages 501-508. MIT press/Badford Books, 1994.
16. N. Monmarché. On data clustering with artificial ants. In A. A. Freitas, editor, AAAI-99 and GECCO-99 Workshop on Data Mining with Evolutionary Algorithms: Research Directions, pages 23-26, Orlando, Florida, 1999.
17. th European Conference ECAL'99, Lecture Notes in Artificial Intelligence 1974, pages 626-635. Swiss Federal Institute of Technology, Lausanne, Switzerland, Springer-Verlag, September 1999.
18. D. J. Newman, S. Hettich, C. L. Blake, and C. J. Merz. UCI repository of machine learning databases. University of California, Irvine, Department of Information and Computer Sciences, 1998. http://www.ics.uci.edu/~mlearn/ MLRepository.html.
19. M. Ono, T. Igarashi, E. Ohno, and M. Sasaki. Unusual thermal defence by a honeybee against mass attack by hornets. Nature, 377(6547):334-336, 1995.
20. S. K. Pal, A. Ghosh, and B. Uma Shankar. Segmentation of remotely sensed images with fuzzy thresholding and quantitative evaluation. International Journal on Remote Sensing, 21(11):2269-2300, 2000.
21. st International Conference on Metaheuristic, Evolutionary and Bio-Inspired Algorithms, pages 284-293, Spain, 2002.
22. V. Ramos, F. Muge, and P. Pina. Self-organized data and image retrieval as a consequence of inter-dynamic synergistic relationships in artificial ant colonies. In J. R. del Solar, A. Abraham, and M. Koppen, editors, Soft-Computing Systems- Design, Management and Applications, Frontiers of Artificial Intelligence and Applications, volume 87, pages 500-509, Amsterdam, 2002. IOS Press.
23. M. Sukama and H. Fukami. Aggregation arrestant pheromone of the German cockroach, Blattella germanica (L.) (Dictyoptera: Blattellidae): isolation and structure elucidation of blasttellastanoside-A and B. Journal of Chemical Ecology, 19:2521-2541, 1993.
24. S. Theodoridis and K. Koutroumbas. Pattern Recognition. Elsevier Academic Press, Amsterdam, second edition, 2003.
25. S. Tsutsui. Ant colony optimization for continuous domains with aggregation pheromones metaphor. In Proceedings of the 5th International Conference on Recent Advances in Soft Computing (RASC'04), pages 207-212, United Kingdom, December 2004.
26. S. Tsutsui and A. Ghosh. An extension of ant colony optimization for function optimization. In Proceedings of the 5th Asia Pacific Conference on Simulated Evolution and Learning (SEAL04), Pusan, Korea, 2004.
27. A. L. Vizini, L. N. de Castro, E. R. Hruschka, and R. R. Gudwin. Towards improving clustering ants: An adaptive ant clustering algorithm. Informatica, 29:143-154, 2005.
28. th International Conference on Machine Learning and Cybernetics, pages 5355-5360, 2005.