An Optimized Inference of Pattern Recognition Using Fuzzy Ant Based Clustering Algorithm

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The tremendous growth in web-based technology, application and sharing of information, and knowledge discovery which have a direct impact on economy, presents voluminous data which require Data Mining Techniques. The current study presents a novel framework of data mining which clusters the data and then follows the Fuzzy Association Rule Mining. The first stage employs the Fuzzy Ant System-Based Clustering Algorithm (FASCA) and Fuzzy Ant K -means (FAK) to cluster the database, while the Fuzzy ant colony system-based Fuzzy Association Rules Mining algorithm can be applied to discover the useful rules for each group. The evaluation revealed that the intended method was not only able to mine the rules much more rapidly, but can also identify more significant rules
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Clustering; Data Mining; Fuzzy Ant Colony System; Fuzzy Association Rule

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Jiawei Han and Micheline Kamber,.:Data Mining Concepts and Techniques‖, ISBN: 978-1-55860-901-3,2006.

Ning Zhong, Yuefeng Li, and Sheng-Tang Wu,” Effective Pattern Discovery for Text Mining.” IEEE transactions on knowledge and data engineering,Vol.21,no. 4,pp:30-44,2012.

Hemlata Sahu, Shalini Shrma, Seema Gondhalakar,” A Brief Overview on Data Mining Survey”, International Journal of Computer Technology and Electronics Engineering,Vol.1,no .3,pp:114-121.

Niknam. F.T, M. Nayeripour and B.Bahmani Firouzi,” Application of a New Hybrid optimization Algorithm on Cluster Analysis”, World Academy of Science, Engineering and Technology 22, pp.589-594,2008.

Anoop Kumar Jain, Satyam Maheswari,” Survey of Recent Clustering Techniques in Data Mining.” International Archive of Applied Sciences and Technology,Vol.3, no.2,pp:68-75,2012.

Rafael S. Parpinelli, Heitor S. Lopes, Member, IEEE, and Alex A. Freitas,” Data Mining With an Ant Colony Optimization Algorithm.” IEEE transactions on evolutionary computing,Vol.6,no. 4,pp 321-332,2002.

Mohamed Jafar O.A & R. Sivakumar,” Ant-based clustering algorithms a brief survey”, International Journal of Computer Theory and Engineering, Vol. 2,no. 5,pp 787-796,2010.

Jiuyong Li , Ada Wai-chee Fu , Paul Fahey,” Efficient discovery of risk patterns in medical data”, Artificial Intelligence in Medicine,2008

Yang, X. B., Sun, J. G., & Huang, D,” A new clustering method based on ant colony algorithm”, Proceedings of 4th world congress intelligent control and automation , pp 2222–222,2002.

Kuo, R.J., Cha, C.L., Chou, S.H., Shih, C.W., & Chiu, C.Y,” Integration of ant algorithm and case based reasoning for knowledge management.”. Proceedings of International Conference on IJIE,, Las Vegas, USA,2003.

Kuo, R.J, S.Y. Lin , C.W. Shih,” Mining association rules through integration of clustering analysis and ant colony system for health insurance database in Taiwan”, Expert Systems with Applications (33),pp 794–808,2007.

Tsai, C. F., Wu, H. C., & Tsai, C. W,” A new clustering approach for data mining in large databases”, Proceedings of international symposium on parallel architectures, algorithms and networks (ISPAN’02) IEEE Computer Society ,pp 1087–4089 ,2002.

Su, B. D. (2002). Discovering association rules through ant systems. Master Thesis of National Chin-Hwa Univeristy, Taiwan, ROC.

Koyuturk, Mehmet, Grama, Ananth, & Ramakrishnan, Naren . Member, compression, clustering and pattern discovery in very highdimensional discrete-attribute data sets. IEEE Transactions on Knowledge and Data Engineering, VOL. 17, NO. 4, pp 447-461,2005.

Maulik, H., & Bandyopadhyay, S. Genetic algorithm-based clustering technique. Pattern Recognition, 33, pp 1455–1465,2000.

Kuo, R. J., Wang, H. S., Hu, T.-L., & Chou, S. H. Application of ant K-means on clustering analysis in data mining. International Journal of Computers and Mathematics with Applications, 50, pp 1709–1724,2005.

Krishna, K., & Murty, M. Genetic K-means algorithm. IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, 29(3),pp 433–439.1999.

Agrawal.R ,R.Sirkant,” Fast algorithms for mining association rules”. Proceedings of 20rd International conference on very large databases, Santiago, Chile,1994

R.Agrawal,T.Imielinski andA. Swami, “Mining association rules between sets of items in large databases,” in: Proc. of ACM SIGMOD conference on management of data, pp. 207-206, 1993.

Mingzan wang, jinzhong he, and yuan xue,” Fault diagnosis based on ant colony optimal Algorithm”, International journal of information and systems sciences,Vol. 1, no. 4, pp 329-338,2005.

A. A. Moghanjoughi, S. Khatun, M. A. Borhanuddin, R. S. A. Raja Abdullah, Performance Analysis of Ant Colony's Algorithm: Load-Balancing in QoS-based for Wireless Mesh Networks Routing, (2008) International Review on Computers and Software (IRECOS), 3. (2), pp. 203 - 209.

M. H. Marghny, A. A. Shakour, Fast, Simple and Memory Efficient Algorithm for Mining Association Rules, (2007) International Review on Computers and Software (IRECOS), 2. (1), pp. 55 - 63.

Francine Krief, Younès Bennani, Danielo Gomes, J. Neuman de Souza , LECSOM: a Low-Energy Routing Algorithm Based on SOM Clustering for Static and Mobile Wireless Sensor Networks, (2011) International Journal on Communications Antenna and Propagation (IRECAP), 1 (1), pp. 55-63.

N. Torabi, M. Karrari, M. B.Menhaj, A Novel Wavelet Fuzzy Fault Location Method for Partially Observable Transmission Networks Based on WAMS/PMU, (2011) International Journal on Communications Antenna and Propagation (IRECAP), 1 (6), pp. 478-487.

T. Shankar, S. Shanmugavel, A. Karthikeyan, Modified Harmony Search Algorithm for Energy Optimization in WSN, (2013) International Journal on Communications Antenna and Propagation (IRECAP), 3 (4), pp. 214-220.


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