Hybrid BAT-PSO optimization techniques for image registration

Manoj, Sumitha; Ranjitha, S.; Suresh, Hasika

doi:10.1109/iceeot.2016.7755375

Cited by 7 publications

(10 citation statements)

References 12 publications

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“…The cooperation between BA and PSO was considered in some previous studies. In ( Manoj et al, 2016 ), an improved version of BA using PSO was proposed to enhance the image registration process for the diagnosis of medical images.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The extensive experimental work in the paper shows that the proposed BPINF can improve the performance of FLAT when applied to many datasets with the variant product of lengths between 25,000 and 21,000,000. BPINF is impartially compared to other known hybrid techniques in literature such as integrated PSO with Ions Motion Optimization (IMO-PSO) (Issa & Abd Elaziz, 2020), Adaptive Sine Cosine Optimization (ASCA-PSO) [9], BA-Cuckoo Search Algorithm (CSA) ( Shehab, Khader, Laouchedi, & Alomari, 2019 ), BA-Differential Evolutionary (DE) ( Yildizdan & Baykan, 2020 ) and two different versions of BA-PSO ( Ferdowsi et al, 2019 , Manoj et al, 2016 ). Moreover, the protein of COVID-19 is investigated against other five viruses, and the LCCS results are reported for many hybrid techniques, as well as the standard SW algorithm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19

Issa

Helmi

Elsheikh

et al. 2022

Expert Systems with Applications

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19

Issa

Helmi

Elsheikh

et al. 2022

Expert Systems with Applications

View full text Add to dashboard Cite

“…Constrained Optimization Zhao et al [146] 2014 HCPSO-IA Complex layout design problems Arunachalam et al [151] 2014 HPSOFF Combined Economic and Emission Dispatch Problem Pan et al [148] 2015 Hybrid PSO-BA Global Optimization Manoj et al [149] 2016 PSO-BA Medical Image Registration Xia et al [150] 2017 FAPSO Global Optimization…”

Section: Author/smentioning

confidence: 99%

Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives

Sengupta

Basak

Peters

2018

MAKE

386

184

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Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social cooperation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment and improvements of its most basic as well as some of the very recent state-of-the-art implementations. Concepts and directions on choosing the inertia weight, constriction factor, cognition and social weights and perspectives on convergence, parallelization, elitism, niching and discrete optimization as well as neighborhood topologies are outlined. Hybridization attempts with other evolutionary and swarm paradigms in selected applications are covered and an up-to-date review is put forward for the interested reader.

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“…An application of a hybrid PSO-BA in medical image registration was demonstrated by Manoj et al [149] where the authors noted that the hybrid algorithm was more successful in finding optimal parameters for the problem as compared to relevant methods already in use.…”

Section: Bat Algorithm (Ba)mentioning

confidence: 99%

“…Author/s: Year Algorithm Area of Application Shi et al [152] 2012 HEPGO Global Optimization El-Shirbiny and Alhamali [147] 2013 HPSIL Fixed Charge Transportation Problems Liu and Zhou [153] 2013 New (GSO-PSO) Constrained Optimization Zhao et al [146] 2014 HCPSO-IA Complex layout design problems Arunachalam et al [151] 2014 HPSOFF Combined Economic and Emission Dispatch Problem Pan et al [148] 2015 Hybrid PSO-BA Global Optimization Manoj et al [149] 2016 PSO-BA Medical Image Registration Xia et al [150] 2017 FAPSO Global Optimization…”

Section: Glow Worm Swarm Optimization (Gso)mentioning

confidence: 99%

Particle Swarm Optimization: A survey of Historical and Recent Developments with Hybridization Perspectives

Sengupta¹,

Basak²,

Peters³

2018

Preprint

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Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment and improvements of its most basic as well as some of the very recent state–of-the-art implementations. Concepts and directions on choosing the inertia weight, constriction factor, cognition and social weights and perspectives on convergence, parallelization, elitism, niching and discrete optimization as well as neighborhood topologies are outlined. Hybridization attempts with other evolutionary and swarm paradigms in selected applications are covered and an up-to-date review is put forward for the interested reader.

show abstract

Hybrid BAT-PSO optimization techniques for image registration

Cited by 7 publications

References 12 publications

A biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19

A biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19

Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives

Particle Swarm Optimization: A survey of Historical and Recent Developments with Hybridization Perspectives

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