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Marine Predator Algorithm for Linear Antenna Arrays Optimization

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Marine Predator Algorithm for Linear Antenna Arrays Optimization
Συγγραφείς: Seyedali Mirjalili
Έτος έκδοσης: 2026
Συλλογή: Torrens University Australia: Figshare
Θεματικοί όροι: Machine learning not elsewhere classified, antenna array optimization, Antenna arrays, Array optimization, Biomimetics, Directional patterns (antenna), linear antenna array, Linear antenna arrays, Marine predatory algorithm, Marine Predatory Algorithm (MPA), metaheuristic algorithm, Meta-heuristics algorithms, nature-inspired optimization, Optimisations, Particle swarm optimization (PSO), pattern synthesis, % reductions, sidelobe level reduction, Sidelobe levels
Περιγραφή: This paper introduces the Marine Predator Algorithm (MPA) for optimal pattern synthesis in linear antenna arrays. Its performance is evaluated in terms of Peak Sidelobe Level (PSLL), mean aperture size, mean amplitude, convergence speed, and radiation pattern. The study also investigates the impact of varying the number of elements in the array and explores two optimization models, including amplitude antenna optimization and position antenna optimization. Simulation results validate the effectiveness of MPA, demonstrating significant improvements over uniform arrays, Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Moth-Flame Optimization (MFO), Cut Swarm Optimization (CSO), and Ant Lion Optimization (ALO). © 2025 IEEE.
Τύπος εγγράφου: conference object
Γλώσσα: unknown
Relation: https://figshare.com/articles/conference_contribution/Marine_Predator_Algorithm_for_Linear_Antenna_Arrays_Optimization/31063612
DOI: 10.1109/CompSysTech65493.2025.11137262
Διαθεσιμότητα: https://doi.org/10.1109/CompSysTech65493.2025.11137262
Rights: CC BY 4.0
Αριθμός Καταχώρησης: edsbas.75CD0244
Βάση Δεδομένων: BASE
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  – Url: https://doi.org/10.1109/CompSysTech65493.2025.11137262#
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  Data: Marine Predator Algorithm for Linear Antenna Arrays Optimization
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  Data: <searchLink fieldCode="AR" term="%22Seyedali+Mirjalili%22">Seyedali Mirjalili</searchLink>
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  Data: 2026
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  Data: Torrens University Australia: Figshare
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  Data: <searchLink fieldCode="DE" term="%22Machine+learning+not+elsewhere+classified%22">Machine learning not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22antenna+array+optimization%22">antenna array optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Antenna+arrays%22">Antenna arrays</searchLink><br /><searchLink fieldCode="DE" term="%22Array+optimization%22">Array optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Biomimetics%22">Biomimetics</searchLink><br /><searchLink fieldCode="DE" term="%22Directional+patterns+%28antenna%29%22">Directional patterns (antenna)</searchLink><br /><searchLink fieldCode="DE" term="%22linear+antenna+array%22">linear antenna array</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+antenna+arrays%22">Linear antenna arrays</searchLink><br /><searchLink fieldCode="DE" term="%22Marine+predatory+algorithm%22">Marine predatory algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Marine+Predatory+Algorithm+%28MPA%29%22">Marine Predatory Algorithm (MPA)</searchLink><br /><searchLink fieldCode="DE" term="%22metaheuristic+algorithm%22">metaheuristic algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Meta-heuristics+algorithms%22">Meta-heuristics algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22nature-inspired+optimization%22">nature-inspired optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Optimisations%22">Optimisations</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization+%28PSO%29%22">Particle swarm optimization (PSO)</searchLink><br /><searchLink fieldCode="DE" term="%22pattern+synthesis%22">pattern synthesis</searchLink><br /><searchLink fieldCode="DE" term="%22%25+reductions%22">% reductions</searchLink><br /><searchLink fieldCode="DE" term="%22sidelobe+level+reduction%22">sidelobe level reduction</searchLink><br /><searchLink fieldCode="DE" term="%22Sidelobe+levels%22">Sidelobe levels</searchLink>
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  Label: Description
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  Data: This paper introduces the Marine Predator Algorithm (MPA) for optimal pattern synthesis in linear antenna arrays. Its performance is evaluated in terms of Peak Sidelobe Level (PSLL), mean aperture size, mean amplitude, convergence speed, and radiation pattern. The study also investigates the impact of varying the number of elements in the array and explores two optimization models, including amplitude antenna optimization and position antenna optimization. Simulation results validate the effectiveness of MPA, demonstrating significant improvements over uniform arrays, Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Moth-Flame Optimization (MFO), Cut Swarm Optimization (CSO), and Ant Lion Optimization (ALO). © 2025 IEEE.
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  Data: https://figshare.com/articles/conference_contribution/Marine_Predator_Algorithm_for_Linear_Antenna_Arrays_Optimization/31063612
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  Data: 10.1109/CompSysTech65493.2025.11137262
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  Data: https://doi.org/10.1109/CompSysTech65493.2025.11137262
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  Data: CC BY 4.0
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1109/CompSysTech65493.2025.11137262
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Machine learning not elsewhere classified
        Type: general
      – SubjectFull: antenna array optimization
        Type: general
      – SubjectFull: Antenna arrays
        Type: general
      – SubjectFull: Array optimization
        Type: general
      – SubjectFull: Biomimetics
        Type: general
      – SubjectFull: Directional patterns (antenna)
        Type: general
      – SubjectFull: linear antenna array
        Type: general
      – SubjectFull: Linear antenna arrays
        Type: general
      – SubjectFull: Marine predatory algorithm
        Type: general
      – SubjectFull: Marine Predatory Algorithm (MPA)
        Type: general
      – SubjectFull: metaheuristic algorithm
        Type: general
      – SubjectFull: Meta-heuristics algorithms
        Type: general
      – SubjectFull: nature-inspired optimization
        Type: general
      – SubjectFull: Optimisations
        Type: general
      – SubjectFull: Particle swarm optimization (PSO)
        Type: general
      – SubjectFull: pattern synthesis
        Type: general
      – SubjectFull: % reductions
        Type: general
      – SubjectFull: sidelobe level reduction
        Type: general
      – SubjectFull: Sidelobe levels
        Type: general
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      – TitleFull: Marine Predator Algorithm for Linear Antenna Arrays Optimization
        Type: main
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              Type: published
              Y: 2026
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