On the performance of newsworthy meta-heuristic algorithms based on point of view fuzzy modelling
Year: 2017
Type: article
Abstract: Heuristic algorithms are used for optimizing a large diversity of engineering problems. In this study, the performance of six commonly used and cited meta-heuristic algorithms (MhAs) is compared based on point of view fuzzy modelling. In this study, the simplest version of MhAs is specifically used to observe and evaluate their natural optimization performances. For the comparisons, dynamic system modelling using a neuro-fuzzy system (NFS) was studied. Obtained results were evaluated based on commonly used statistical metrics, and then each algorithm was ranked according to these metrics. Based on the computed average ranks, the best MhA among the six MhAs was identified, and the effect of MhAs on fuzzy modelling was investigated.
DOI: 10.3906/elk-1705-337
Author: Cihan KARAKUZU
Institution: Bilecik Şeyh Edebali Üniversitesi
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2772621479