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MJS: a modified artificial jellyfish search algorithm for continuous optimization problems

Neural Computing and Applications · Şubat 2023

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YÖKSİS Kayıtları
MJS: a modified artificial jellyfish search algorithm for continuous optimization problems
Neural Computing and Applications · 2023 SCI-Expanded
Dr. Öğr. Üyesi GÜLNUR YILDIZDAN →
YÖKSİS ISSN Eşleşmesi

Bu dergide (ISSN eşleşmesi) kurumun 20 kaydı bulundu.

YÖKSİS Kayıtları — ISSN Eşleşmesi
Automatic detection and classification of rotor cage faults in squirrel cage induction motor
2010 ISSN: 0941-0643 SCI-Expanded 6 atıf
Prof. Dr. HAYRİ ARABACI →
Short term load forecasting using fuzzy logic and ANFIS
2015 ISSN: 0941-0643 SCI-Expanded 1 atıf
Dr. Öğr. Üyesi HASAN HÜSEYİN ÇEVİK →
Determination of induction motor parameters with differential evolution algorithm
2012 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Short term load forecasting using fuzzy logic and ANFIS
2015 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Fuzzy logic based induction motor protection system
2013 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Determination of induction motor parameters with differential evolution algorithm
2012 ISSN: 0941-0643 SCI-Expanded
Doç. Dr. TAHİR SAĞ →
Cost optimization of mixed feeds with the particle swarm optimization method
2013 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
A combination of Genetic Algorithm Particle Swarm Optimization and Neural Network for palmprint recognition
2013 ISSN: 0941-0643 SCI-Expanded 1 atıf
Prof. Dr. ADEM ALPASLAN ALTUN →
Cost optimization of mixed feeds with the particle swarm optimization method
2013 ISSN: 0941-0643 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
Fuzzy logic based induction motor protection system
2013 ISSN: 0941-0643 SCI
Dr. Öğr. Üyesi OKAN UYAR →
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
2018 ISSN: 0941-0643 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
FPGA based self organizing fuzzy controller for electromagnetic filter
2016 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
FPGA-based self-organizing fuzzy controller for electromagnetic filter
2017 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
A new MILP model proposal in feed formulation and using a hybrid linear binary PSO H LBP approach for alternative solutions
2016 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
Application of fuzzy C-means clustering algorithm to spectral features for emotion classification from speech
2018 ISSN: 0941-0643 SCI-Expanded Q1
Prof. Dr. HUMAR KAHRAMANLI ÖRNEK →
A new denoising method for fMRI based on weighted three-dimentional wavelet transform
2018 ISSN: 0941-0643 SCI-Expanded
Dr. Öğr. Üyesi GÜZİN ÖZMEN →
FPGA-based self-organizing fuzzy controller for electromagnetic filter
2017 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions
2018 ISSN: 0941-0643 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
Hybrid breast cancer detection tem via neural network and feature ion based on SBS SFS and PCA
2013 ISSN: 0941-0643 SCI-Expanded 5 atıf
Dr. Öğr. Üyesi ONUR İNAN →
FPGA-based self-organizing fuzzy controller for electromagnetic filter
2017 ISSN: 0941-0643 SCI-Expanded
Doç. Dr. İLKER ALİ ÖZKAN →

Makale Bilgileri

Dergi Neural Computing and Applications
ISSN09410643
Yayın TarihiŞubat 2023
Cilt / Sayfa35 · 3483-3519
DOI10.1007/s00521-022-07842-w
Scopus ID2-s2.0-85139972606
Özet Artificial jellyfish search algorithm (JS) is a recently proposed optimization algorithm inspired by the search behavior of jellyfish in the ocean. There are two different search behaviors in JS: the motion of the jellyfish due to ocean currents (global search) and the motion of the jellyfish within the swarm (local search). In this study, two modifications, one in the local and the other in the global search formula, were made to strengthen the search capability of the standard algorithm. By means of the modification made in the global search, the search direction was directed toward the best and elite set individuals and higher quality solutions were found. A more detailed search around the individuals and the longer preservation of diversity in the population were ensured by another modification to the local search. In addition, it was studied to find the most ideal value for the time control mechanism that provides the transition between local and global search. The new modified algorithm (MJS), obtained as a result of all these modifications, was tested on a total of eighty minimization problems, including standard benchmark functions, Congress of Evolutionary Computation 2013 (CEC2013) test function, and Congress of Evolutionary Computation 2017 (CEC2017) test functions. The results of these tests for different dimensions were compared to the standard JS algorithm and the algorithms selected from the literature. Also, the results were interpreted by means of statistical tests. These comparisons and statistical tests showed that the proposed MJS algorithm produced acceptable, successful, and competitive results.

Yazarlar (1)

1
Gülnur Yildizdan

Anahtar Kelimeler

Artificial jellyfish search algorithm Continuous optimization Global optimization Heuristic algorithms

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Neural Computing and Applications
Q1
SJR Skoru1,102
H-Index146
YayıncıSpringer London
ÜlkeUnited Kingdom
Artificial Intelligence (Q1)
Software (Q1)
Dergi sayfasına git

Metrikler

10
Atıf
1
Yazar
4
Anahtar Kelime

Sistemimizdeki Yazarlar

GY
GÜLNUR YILDIZDAN
Dr. Öğr. Üyesi

Hızlı Erişim

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