Data Clustering Using Moth-Flame Optimization Algorithm

A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers. Besides, due to weak exploration capability, it is easily stuck at local optima. Recently, a new metaheuristic called Moth...

詳細記述

書誌詳細

主要な著者:	Tribhuvan Singh, Nitin Saxena, Manju Khurana, Dilbag Singh, Mohamed Abdalla, Hammam Alshazly
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2021-06-01
シリーズ:	Sensors
主題:	data clustering data mining k-means moth flame optimization meta-heuristic
オンライン･アクセス:	https://www.mdpi.com/1424-8220/21/12/4086
タグ:	タグ追加 タグなし, このレコードへの初めてのタグを付けませんか!