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PVS: a new population-based vortex search algorithm with boosted exploration capability using polynomial mutation

Neural Computing and Applications · Ocak 2022

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YÖKSİS Kayıtları
PVS: a new population-based vortex search algorithm with boosted exploration capability using polynomial mutation
Neural Computing and Applications · 2022 SCI-Expanded
Doç. Dr. TAHİR SAĞ →
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 TarihiOcak 2022
DOI10.1007/s00521-022-07671-x
Scopus ID2-s2.0-85136222809
Özet This paper introduces a novel population-based vortex search algorithm (PVS) to improve the weakness of the global search capability of the original Vortex Search (VS) algorithm which is a simple and efficient physics-based metaheuristic and originally has a single-solution-based structure. Single-solution-based metaheuristics perform a local search in the neighborhood of a single solution, whereas population-based metaheuristics conduct the search process by creating several candidate solutions at different points in the search space. The fast-running structures of single-solution-based algorithms may cause the search process to get stuck in the local optimum in some cases. The proposed algorithm transforms VS into a population-based structure with a location update operator and the polynomial mutation operator. Also, the strategy of generating solutions based on the radius reduction mechanism around a center is maintained. Furthermore, two variants of PVS, called PVS_a and PVS_b, are presented in this study. The performance of the proposed approach is investigated by applying a set of experimental series. Three different benchmark sets involving (i) 20 classical benchmark functions, (ii) 29 CEC2017 test functions, and (iii) 10 CEC2019 test functions are employed in experiments. In addition, four real-world-constrained optimization problems are used to evaluate the effectiveness of PVS. Considering the experimental results obtained from the comparison of the proposed algorithm with both state-of-the-art and recent metaheuristics, the developed PVS_a algorithm provides highly quite promising and superior outcomes in solution quality and robustness.

Yazarlar (1)

1
Tahir Saǧ

Anahtar Kelimeler

Metaheuristic algorithms Numerical optimization PVS Vortex search optimization

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

21
Atıf
1
Yazar
4
Anahtar Kelime

Sistemimizdeki Yazarlar

TS
TAHİR SAĞ
Doç. Dr.

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