Quantum-inspired adaptive mutation operator enabled PSO (QAMO-PSO) for parallel optimization and tailoring parameters of Kolmogorov–Arnold network

Particle swarm optimizer (PSO) is a biomimetic optimization algorithm well-known for its potential in addressing diversified optimization problems (OP). Although PSO is based on swarm-cognitive, it often suffers from attaining the global optima and the balance between exploration and exploitation, l...

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Bibliographic Details
Published in:	The Journal of supercomputing Vol. 81; no. 14; p. 1310
Main Authors:	Agrawal, Umang Kumar, Panda, Nibedan
Format:	Journal Article
Language:	English
Published:	New York Springer US 06.09.2025 Springer Nature B.V
Subjects:	Algorithms Cognition Compilers Computer Science Convergence Datasets Genetic algorithms Interpreters Methods Mutation Numerical analysis Optimization algorithms Particle swarm optimization Physics Processor Architectures Programming Languages Qubits (quantum computing) Statistical analysis Swarm intelligence Quantum adaptive mutation operator Kolmogorov–Arnold network Qubit Particle swarm optimization Hybrid algorithm
ISSN:	1573-0484, 0920-8542, 1573-0484
Online Access:	Get full text
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