Design and application of nature inspired computing approach for nonlinear stiff oscillatory problems

Junaid Ali Khan, Muhammad Asif Zahoor Raja, Muhammed I. Syam, Shujaat Ali Khan Tanoli, Saeed Ehsan Awan

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)

Abstract

In this paper, meta-heuristic intelligent approaches are developed for handling nonlinear oscillatory problems with stiff and non-stiff conditions. The mathematical modeling of these oscillators is accomplished using feed-forward artificial neural networks (ANNs) in the form of an unsupervised manner. The accuracy as well as efficiency of the model is subject to the tuning of adaptive parameters for ANNs that are highly stochastic in nature. These optimal weights are carried out with swarm intelligence and pattern search methods hybridized with an efficient local search technique based on constraints minimization known as active set algorithm. The proposed schemes are validated on various stiff and non-stiff variants of the oscillator. The significance, applicability and reliability of the proposed scheme are well established based on comparison made with the results of standard numerical solver.

Original languageEnglish
Pages (from-to)1763-1780
Number of pages18
JournalNeural Computing and Applications
Volume26
Issue number7
DOIs
Publication statusPublished - Oct 21 2015

Keywords

  • Active set algorithm
  • Neural networks
  • Pattern search
  • Swarm intelligence
  • Van der Pol oscillators

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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