Clustering Method Based on Artificial Algae Algorithm
DOI:
https://doi.org/10.18201/ijisae.2021473632Keywords:
×Optimization×, Clustering, OptimizationAbstract
For decades, the researchers have developed many ways as optimization procedures with the aim of find the best solution in short time for a many problems under certain conditions in the field of engineering, medicine and banking. These ways have been also used for parameter updating of algorithms. The most popular Optimization algorithms methods known are mining classification and clustering. In this article, the clustering has been used to identify the most important point in the best cluster centers of set data. Artificial Algae Algorithm (AAA) optimization algorithm was used in the clustering process and implemented on UCI datasets. Balance, Breast Cancer Wisconsin Diagnostic, Breast Cancer Wisconsin original, Pima Diabetes, Glass, Iris, Wine, Urban Land Cover and Hill Valley UCI datasets are used to assess the performing of the Algae Algorithm-based clustering algorithm. Euclides method was used to calculate the distance between the data. The performance of the AAA based clustering algorithm, Total square distance values in different iteration numbers were calculated for each data set. The total square error rate value was calculated for each iteration and as the number of iterations progresses, the total square error rate value decreases smoothly. The results obtained were compared with k-means, Differential Evolution (DE), Genetic Algorithm (GA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA) clustering algorithms. According to the experimental results in this study, the proposed AAA-based clustering algorithm achieved better results in iris and wine data sets compared to other clustering algorithms, while it obtained close to good results in other data sets. As a result, the Artificial Algae Algorithm-based clustering algorithm showed that the method showed a fairly stable appearance and the performance of the clusters also increased, which shows that this study successfully achieved its purpose.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.