Title
Design of Morlet wavelet neural network for solving the higher order singular nonlinear differential equations
Date Issued
01 December 2021
Access level
open access
Resource Type
research article
Author(s)
Nisar K.
Raja M.A.Z.
Ibrahim A.A.B.A.
Rodrigues J.J.P.C.
Al-Basyouni K.S.
Mahmoud S.R.
Rawat D.B.
Abstract
The aim of this study is to present the numerical solutions of the higher order singular nonlinear differential equations using an advanced intelligent computational approach by manipulating the Morlet wavelet (MW) neural networks (NNs), global approach as genetic algorithm (GA) and quick local search approach as interior-point method (IPM), i.e., GA-IPM. MWNNs is applied to discretize the higher order singular nonlinear differential equations to express the activation function using the mean square error. The performance of the designed MWNNs using the GA-IPM is observed to solve three different variants based on the higher order singular nonlinear differential model to check the significance, efficacy and consistency of the designed MWNNs using the GA-IPM. Furthermore, statistical performances are provided to check the precision, accuracy and convergence of the present approach.
Start page
5935
End page
5947
Volume
60
Issue
6
Language
English
OCDE Knowledge area
Ciencias de la computación
Subjects
Scopus EID
2-s2.0-85107933179
Source
Alexandria Engineering Journal
ISSN of the container
11100168
Sponsor(s)
The paper collaboration among University Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia, Howard University, Washington, DC, USA, King Abdulaziz University, Jeddah, Saudi Arabia, Hazara University, Mansehra, Pakistan, Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C., Federal University of Piauí (UFPI), Teresina - PI, Brazil, and Instituto de Telecomunicações, 6201-001 Covilhã, Portugal. The authors would like to thanks Professor Dr. Yong-Jin Park (IEEE Life member) Former Director IEEE Region 10 for his expertise, his valuable comments and suggestions to improve the quality of the paper. This work was supported by the Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, Malaysia. Furthermore, this work is partially funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the Project UIDB/50008/2020; and by Brazilian National Council for Scientific and Technological Development - CNPq, via Grant No. 313036/2020-9.
The paper collaboration among University Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia, Howard University, Washington, DC, USA, King Abdulaziz University, Jeddah, Saudi Arabia, Hazara University, Mansehra, Pakistan, Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C. Federal University of Piau? (UFPI), Teresina - PI, Brazil, and Instituto de Telecomunica??es, 6201-001 Covilh?, Portugal. The authors would like to thanks Professor Dr. Yong-Jin Park (IEEE Life member) Former Director IEEE Region 10 for his expertise, his valuable comments and suggestions to improve the quality of the paper. This work was supported by the Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, Malaysia. Furthermore, this work is partially funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the Project UIDB/50008/2020; and by Brazilian National Council for Scientific and Technological Development - CNPq, via Grant No. 313036/2020-9.
Sources of information:
Directorio de Producción Científica
Scopus