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Media type:
E-Article
Title:
A neuro-swarming intelligent heuristic for second-order nonlinear Lane–Emden multi-pantograph delay differential system
Contributor:
Sabir, Zulqurnain;
Raja, Muhammad Asif Zahoor;
Le, Dac-Nhuong;
Aly, Ayman A.
imprint:
Springer Science and Business Media LLC, 2022
Published in:
Complex & Intelligent Systems, 8 (2022) 3, Seite 1987-2000
Language:
English
DOI:
10.1007/s40747-021-00389-8
ISSN:
2199-4536;
2198-6053
Origination:
Footnote:
Description:
<jats:title>Abstract</jats:title><jats:p>The current study is related to present a novel neuro-swarming intelligent heuristic for nonlinear second-order Lane–Emden multi-pantograph delay differential (NSO-LE-MPDD) model by applying the approximation proficiency of artificial neural networks (ANNs) and local/global search capabilities of particle swarm optimization (PSO) together with efficient/quick interior-point (IP) approach, i.e., ANN-PSOIP scheme. In the designed ANN-PSOIP scheme, a merit function is proposed by using the mean square error sense along with continuous mapping of ANNs for the NSO-LE-MPDD model. The training of these nets is capable of using the integrated competence of PSO and IP scheme. The inspiration of the ANN-PSOIP approach instigates to present a reliable, steadfast, and consistent arrangement relates the ANNs strength for the soft computing optimization to handle with such inspiring classifications. Furthermore, the statistical soundings using the different operators certify the convergence, accurateness, and precision of the ANN-PSOIP scheme.</jats:p>