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Original Research ARTICLE

Front. Phys. | doi: 10.3389/fphy.2020.00224

A neuro-swarming intelligence based computing for second order singular periodic nonlinear boundary value problems Provisionally accepted The final, formatted version of the article will be published soon. Notify me

  • 1Universidad Politécnica de Cartagena, Spain
  • 2Hazara University, Pakistan
  • 3National Yunlin University of Science and Technology, Taiwan
  • 4COMSATS University, Islamabad Campus, Pakistan

In the present investigation, a novel neuro-swarming intelligence-based numerical computing solver is developed for solving second order nonlinear singular periodic (NSP) boundary value problems (BVPs), i.e., NSP-BVPs, using modeling strength of artificial neural networks (ANN) optimized with global search efficacy of particle swarm optimization (PSO) supported with the methodology of rapid local search by interior-point scheme (IPS), i.e., ANN-PSO-IPS. In order to check the proficiency, robustness and stability of the designed ANN-PSO-IPS, two numerical problems of the NSP-BVPs have been presented for different number of neurons. The outcomes of proposed ANN-PSO-IPS are compared with the available exact solutions to establish worth of the solver in terms of accuracy and convergence, which is further endorsed through results of statistical performance metrics based on multiple implementations.

Keywords: Singular periodic systems, Particle Swarm Optimization, Hybrid approach, Interior-point scheme, artificial neural networks, statistical analysis

Received: 21 Apr 2020; Accepted: 25 May 2020.

Copyright: © 2020 GUIRAO, Sabir, Raja and Shoaib. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. JUAN L. G. GUIRAO, Universidad Politécnica de Cartagena, Cartagena, Spain, juan.garcia@upct.es