Novel computing paradigms for parameter estimation in power signal models View Full Text


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Article Info

DATE

2019-03-12

AUTHORS

Ammara Mehmood, Naveed Ishtiaq Chaudhary, Aneela Zameer, Muhammad Asif Zahoor Raja

ABSTRACT

The strength of evolutionary computational heuristic paradigms is exploited for parameter estimation of power signal modeling problems by incorporating differential evolution (DE), genetic algorithms (GAs) and pattern search (PS) methodologies. The objective function of power signal harmonics is constructed by utilizing the power of approximation theory in mean squared error sense. The stiff optimization task of signal harmonics is performed with heuristic solvers DE, GAs and PS that provide efficacy, fast convergence rate and avoid getting trapped in local minima. Statistics reveal that DE outperforms its counterparts in terms of accuracy, robustness and complexity measures. More... »

PAGES

1-30

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    URI

    http://scigraph.springernature.com/pub.10.1007/s00521-019-04133-9

    DOI

    http://dx.doi.org/10.1007/s00521-019-04133-9

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    https://app.dimensions.ai/details/publication/pub.1112703107


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