The chapter will describe the potential of the swarm intelligence and in particular quantum PSO-based algorithm, to solve complicated electromagnetic problems. This task is accomplished through addressing the design and analysis challenges of some key real-world problems. A detailed definition of the conventional PSO and its quantum-inspired version are presented and compared in terms of accuracy and computational burden. Some theoretical discussions concerning the convergence issues and a sensitivity analysis on the parameters influencing the stochastic process are reported.

Swarm Intelligence for Electromagnetic Problem Solving / Mescia, Luciano; Bia, Pietro; Caratelli, Diego; Gielis, Johan. - (2017), pp. 69-100. [10.4018/978-1-5225-2128-0.ch003]

Swarm Intelligence for Electromagnetic Problem Solving

MESCIA, Luciano;BIA, Pietro;
2017-01-01

Abstract

The chapter will describe the potential of the swarm intelligence and in particular quantum PSO-based algorithm, to solve complicated electromagnetic problems. This task is accomplished through addressing the design and analysis challenges of some key real-world problems. A detailed definition of the conventional PSO and its quantum-inspired version are presented and compared in terms of accuracy and computational burden. Some theoretical discussions concerning the convergence issues and a sensitivity analysis on the parameters influencing the stochastic process are reported.
2017
Handbook of Research on Soft Computing and Nature-Inspired Algorithms
9781522521280
9781522521297
IGI Global
Swarm Intelligence for Electromagnetic Problem Solving / Mescia, Luciano; Bia, Pietro; Caratelli, Diego; Gielis, Johan. - (2017), pp. 69-100. [10.4018/978-1-5225-2128-0.ch003]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/106234
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