A new hybrid approach for solving partial differential equations: Combining Physics-Informed Neural Networks with Cat-and-Mouse based Optimization

A new hybrid approach for solving partial differential equations: Combining Physics-Informed Neural Networks with Cat-and-Mouse based Optimization

Partial differential equations (PDEs) are essential for modeling a wide range of physical phenomena. Physics-Informed Neural Networks (PINNs) offer a promising numerical framework for solving PDEs, but their performance often depends on the choice of optimization strategy and network configuration....

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Bibliographic Details
Main Authors: Nursyiva Irsalinda, Maharani A. Bakar, Fatimah Noor Harun, Sugiyarto Surono, Danang A. Pratama
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Results in Applied Mathematics
Subjects:
Artificial neural networks
Physic-Informed Neural Networks
Cat and mouse based optimizer
Hybrid
Partial differential equations
Online Access:http://www.sciencedirect.com/science/article/pii/S2590037425000032

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http://www.sciencedirect.com/science/article/pii/S2590037425000032

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