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Author Mescia, L.; Bia, P.; Gielis, J.; Caratelli, D. url  doi
openurl 
  Title Advanced particle swarm optimization methods for electromagnetics Type P1 Proceeding
  Year (down) 2023 Publication Abbreviated Journal  
  Volume Issue Pages 109-122 T2 - Proceedings of the 1st International  
  Keywords P1 Proceeding; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)  
  Abstract Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos Publication Date 2023-11-29  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-90-833839-0-3 ISBN Additional Links UA library record  
  Impact Factor Times cited Open Access  
  Notes Approved Most recent IF: NA  
  Call Number UA @ admin @ c:irua:201048 Serial 9002  
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