Multi-population Black Hole Algorithm for the problem of data clustering.

ABSTRACT: The retrieval of important information from a dataset requires applying a special data mining technique known as data clustering (DC). DC classifies similar objects into a groups of similar characteristics. Clustering involves grouping the data around k-cluster centres that typically are selected randomly. Recently, the issues behind DC have called for a search for an alternative solution. Recently, a nature-based optimization algorithm named Black Hole Algorithm (BHA) was developed to address the several well-known optimization problems. The BHA is a metaheuristic (population-based) that mimics the event around the natural phenomena of black holes, whereby an individual star represents the potential solutions revolving around the solution space. The original BHA algorithm showed better pe

SUBMITTER: Salih SQ 

PROVIDER: S-EPMC10321652 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature