Community Detection Using Central Force Optimization (CFO)

ANUPAM, BISWAS and BHASKAR, BISWAS and BISWAS, AGARWAL and SANTOSH, KUMAR CHOURASIA and SIDDHARTHA K, ARJARIA (2017) Community Detection Using Central Force Optimization (CFO). In: Sixth International Conference on Advances in Computing, Control and Networking - ACCN 2017, 25-26 February 2017, Bangkok, Thailand.

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Abstract

Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. . In this paper Central Force Optimization (CFO), physics based optimization, and its variants are used to detect communities. CFO is deterministic in nature, unlike the most widely used meta-heuristics. However, CFO is not free from the problem of premature convergence. Therefore the variants used Adaptive CFO (ACFO) and Multi-Start CFO (MCFO) are used in enhancing the convergence.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Community Detection, Physics Inspired Optimization, CF, Social Network Analysis.
Depositing User: Mr. John Steve
Date Deposited: 16 Mar 2019 12:30
Last Modified: 16 Mar 2019 12:30
URI: http://publications.theired.org/id/eprint/559

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