Abstract
In this paper, An AABC-based Optimized Data Clustering technique using cellular automata in data mining is proposed. In our previous work, Adaptive Central Force Optimization (ACFO) was utilized but it lacks in performance measures. To improve the performance measures in the proposed data clustering technique, AABC is utilized to predict the threshold. The efficiency of the projected technique is analyzed with the help of the brain MR images to cluster the tumour parts in the images. The efficiency of the projected AABC technique is compared with the existing ACFO technique. Also, benchmark functions are utilized to assess the clustering performance of the projected technique.
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Srinivasa Rao, G., Sudhakar, P. (2020). A New Adaptive Artificial Bee Colony (AABC) Technique in Cellular Automata Data Clustering. In: Satapathy, S., Bhateja, V., Mohanty, J., Udgata, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 160. Springer, Singapore. https://doi.org/10.1007/978-981-32-9690-9_1
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DOI: https://doi.org/10.1007/978-981-32-9690-9_1
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