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

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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.

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Authors and Affiliations

  1. Faculty of Engineering Science and Technology, Hamdard University, Islamabad Campus, Islamabad, Pakistan

    Junaid Ali Khan

  2. Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan

    Muhammad Asif Zahoor Raja, Shujaat Ali Khan Tanoli & Saeed Ehsan Awan

  3. Department of Mathematical Sciences, UAE University, Al-Ain, Box 1551, UAE

    Muhammed I. Syam

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  1. Junaid Ali Khan
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Correspondence to Muhammad Asif Zahoor Raja.

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Khan, J.A., Raja, M.A.Z., Syam, M.I. et al. Design and application of nature inspired computing approach for nonlinear stiff oscillatory problems. Neural Comput & Applic 26, 1763–1780 (2015). https://doi.org/10.1007/s00521-015-1841-z

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