DESIGN OF NEURO-SWARMING HEURISTIC SOLVER FOR MULTI-PANTOGRAPH SINGULAR DELAY DIFFERENTIAL EQUATION

Zulqurnain Sabir (), Dumitru Baleanu, Muhammad Asif Zahoor Raja and Juan L. G. Guirao ()
Additional contact information
Zulqurnain Sabir: Department of Mathematics and Statistics, Hazara University, Mansehra, Pakistan
Dumitru Baleanu: ��Department of Mathematics, Cankaya University, Ankara, Turkey‡Institute of Space Science, Magurele-Bucharest, Romania§Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
Muhammad Asif Zahoor Raja: �Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C.∥Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan
Juan L. G. Guirao: *Department of Applied Mathematics and Statistics, Technical University of Cartagena, Hospital de Marina 30203-Cartagena, Spain

FRACTALS (fractals), 2021, vol. 29, issue 05, 1-16

Abstract: This research work is to design a neural-swarming heuristic procedure for numerical investigations of Singular Multi-Pantograph Delay Differential (SMP-DD) equation by applying the function approximation aptitude of Artificial Neural Networks (ANNs) optimized efficient swarming mechanism based on Particle Swarm Optimization (PSO) integrated with convex optimization with Active Set (AS) algorithm for rapid refinements, named as ANN-PSO-AS. A merit function (MF) on mean squared error sense is designed by using the differential ANN models and boundary condition. The optimization of this MF is executed with the global PSO and local search AS approaches. The planned ANN-PSO-AS approach is instigated for three different SMP-DD model-based equations. The assessment with available standard results relieved the effectiveness, robustness and precision that is further authenticated through statistical investigations of Variance Account For, Root Mean Squared Error, Semi-Interquartile Range and Theil’s inequality coefficient performances.

Keywords: Multi-pantograph Systems; Particle Swarm Optimization; Neural Networks; Active-set Algorithm; Numerical Computing; Statistical Measures (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X21400223
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:29:y:2021:i:05:n:s0218348x21400223

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X21400223

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().