دورية أكاديمية
Data Clustering Using Moth-Flame Optimization Algorithm
| العنوان: | Data Clustering Using Moth-Flame Optimization Algorithm |
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| المؤلفون: | Tribhuvan Singh, Nitin Saxena, Manju Khurana, Dilbag Singh, Mohamed Abdalla, Hammam Alshazly |
| المصدر: | Sensors, Vol 21, Iss 12, p 4086 (2021) |
| بيانات النشر: | MDPI AG, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Chemical technology |
| مصطلحات موضوعية: | data clustering, data mining, k-means, moth flame optimization, meta-heuristic, Chemical technology, TP1-1185 |
| الوصف: | 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 Flame Optimizer (MFO) is proposed to handle complex problems. MFO simulates the moths intelligence, known as transverse orientation, used to navigate in nature. In various research work, the performance of MFO is found quite satisfactory. This paper suggests a novel heuristic approach based on the MFO to solve data clustering problems. To validate the competitiveness of the proposed approach, various experiments have been conducted using Shape and UCI benchmark datasets. The proposed approach is compared with five state-of-art algorithms over twelve datasets. The mean performance of the proposed algorithm is superior on 10 datasets and comparable in remaining two datasets. The analysis of experimental results confirms the efficacy of the suggested approach. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 21124086 1424-8220 |
| Relation: | https://www.mdpi.com/1424-8220/21/12/4086; https://doaj.org/toc/1424-8220 |
| DOI: | 10.3390/s21124086 |
| URL الوصول: | https://doaj.org/article/bb3fd51af86e4c3e92b5d4f645ff51ee |
| رقم الأكسشن: | edsdoj.bb3fd51af86e4c3e92b5d4f645ff51ee |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 21124086 14248220 |
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| DOI: | 10.3390/s21124086 |