A SURVEY ON VARIOUS CLUSTERING ALGORITHMS USING NATURE INSPIRED ALGORITHMS

Authors:

Mohammed Ali Shaik ,P. Praveen,

DOI NO:

https://doi.org/10.26782/jmcms.2020.07.00023

Keywords:

Swarm intelligence,Machine learning, K-means,Bio-inspired algorithms,Intelligent algorithms, Literature review,Nature-inspired computing,

Abstract

K-means clustering algorithm and its variants have many drawbacks and one of the major one is getting stuck at local optima while calculating centroids over random values. Algorithms that optimize computation are iterative in nature for speeding up the process of creation or search of data by multiple search agents. Swarm intelligence (SI), is a primary aspect of artificial intelligence that comprises of high complexity problems and proposed solutions that are sub-optimal and achievable in a given time span. SI adopts cooperative character of an organized group of animals that are formed on the phrase: strive to survive and in this paper we provide a detailed survey of eight different SI algorithms that are related to insect and animal based algorithms and provides initial understanding and exploring of technical aspects of algorithms.

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