Novel design of Morlet wavelet neural network for solving second order Lane-Emden equation
| Autor: | Mehmet Giyas Sakar, Hafiz Abdul Wahab, Muhammad Asif Zahoor Raja, Zulqurnain Sabir, Muhammad Umar |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Numerical Analysis
Correctness General Computer Science Artificial neural network business.industry Computer science Applied Mathematics 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Theoretical Computer Science Morlet wavelet Modeling and Simulation Genetic algorithm Convergence (routing) 0202 electrical engineering electronic engineering information engineering Applied mathematics 020201 artificial intelligence & image processing Local search (optimization) 0101 mathematics Lane–Emden equation business Nash–Sutcliffe model efficiency coefficient |
| Popis: | In this study, a novel computational paradigm based on Morlet wavelet neural network (MWNN) optimized with integrated strength of genetic algorithm (GAs) and Interior-point algorithm (IPA) is presented for solving second order Lane-Emden equation (LEE). The solution of the LEE is performed by using modelling of the system with MWNNs aided with a hybrid combination of global search of GAs and an efficient local search of IPA. Three variants of the LEE have been numerically evaluated and their comparison with exact solutions demonstrates the correctness of the presented methodology. The statistical analyses are performed to establish the accuracy and convergence via the Theil's inequality coefficient, mean absolute deviation, and Nash Sutcliffe efficiency based metrics. (C) 2020 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. |
| Databáze: | OpenAIRE |
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