Staff Members - Benha University
Intelligent computing technique for solving singular multi-pantograph delay differential equation
Soft Computing • 2022
Publication Information
Authors
Zulqurnain Sabir1
• Hafiz Abdul Wahab1
• Tri Gia Nguyen2
• Gilder Cieza Altamirano3
•
Fevzi Erdog˘ an4
• Mohamed R. Ali5,6
Keywords
Not Available
Journal
Soft Computing
Publisher
springer
Volume
2022
Issue
Not Available
Pages
Not Available
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
The purpose of this study is to introduce a stochastic computing solver for the multi-pantograph delay differential equation
(MP-DDE). The MP-DDE is not easy to solve due to the singularities and pantograph terms. An advance computational
intelligent paradigm is proposed to solve MP-DDE of the second kind by manipulating the procedures of the artificial
neural networks (ANNs) through the optimization of genetic algorithm (GA) and sequential quadratic programming (SQP),
i.e., ANNs-GA-SQP. A fitness function is constructed based on MP-DDE of second kind and corresponding boundary
conditions. The correctness of the ANNs-GA-SQP is observed by performing the comparison of the proposed and exact
solutions. The values of the absolute error (AE) in good measures are provided to solve the MP-DDE of the second kind.
The efficacy and correctness of the stochastic computing approach to solve three problems of the MP-DDE of second kind
to signify the efficiency, worth, and consistency. Moreover, the statistical soundings are applied to validate the accuracy
and consistency.
(MP-DDE). The MP-DDE is not easy to solve due to the singularities and pantograph terms. An advance computational
intelligent paradigm is proposed to solve MP-DDE of the second kind by manipulating the procedures of the artificial
neural networks (ANNs) through the optimization of genetic algorithm (GA) and sequential quadratic programming (SQP),
i.e., ANNs-GA-SQP. A fitness function is constructed based on MP-DDE of second kind and corresponding boundary
conditions. The correctness of the ANNs-GA-SQP is observed by performing the comparison of the proposed and exact
solutions. The values of the absolute error (AE) in good measures are provided to solve the MP-DDE of the second kind.
The efficacy and correctness of the stochastic computing approach to solve three problems of the MP-DDE of second kind
to signify the efficiency, worth, and consistency. Moreover, the statistical soundings are applied to validate the accuracy
and consistency.