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Abstract
A new efficient optimization method, called ‘Teaching–Learning-Based Optimization (TLBO)’, has been proposed very recently for the optimization of mechanical design problems. This paper proposes a new approach to using TLBO to cluster data. It is shown how TLBO can be used to find the centroids of a user specified number of clusters. The new TLBO algorithms are evaluated on some datasets and compared to the performance of K-means and PSO clustering. Results show that TLBO clustering techniques have much potential.
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Authors and Affiliations
Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India
Suresh Chandra Satapathy
Majhighariani Institute of Technology and Sciences, Rayagada, India
Anima Naik
- Suresh Chandra Satapathy
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- Anima Naik
Search author on:PubMed Google Scholar
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Editors and Affiliations
Department of Electrical Engineering, IIT, Delhi, India
Bijaya Ketan Panigrahi
School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore
Ponnuthurai Nagaratnam Suganthan
Department of Electronics and Telecommunications, Jadavpur University, 700032, Kolkata, India
Swagatam Das
ANITS, Visakhapatnam, India
Suresh Chandra Satapathy
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Satapathy, S.C., Naik, A. (2011). Data Clustering Based on Teaching-Learning-Based Optimization. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_18
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