Metaheuristic optimisation methods for approximate solving of singular boundary value problems-Reference-Cited by-同舟云学术

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Metaheuristic optimisation methods for approximate solving of singular boundary value problems

Published:2016-11-23 Issue:4 Volume:29 Page:823-842
ISSN:0952-813X
Container-title:Journal of Experimental & Theoretical Artificial Intelligence
language:en
Short-container-title:Journal of Experimental & Theoretical Artificial Intelligence

Author:

Sadollah Ali¹^ORCID,Yadav Neha²,Gao Kaizhou³,Su Rong⁴

Affiliation:

1. Young Researchers and Elites club, Science and Research Branch, Islamic Azad University, Tehran, Iran

2. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul 02841, South Korea

3. School of Computer, Liaocheng University, Liaocheng 252000, China

4. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore

Funder

The Economic Development Board, Singapore, for the project of “Development of NTU/NXP Smart Mobility Test-bed”.

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Theoretical Computer Science,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2016.1259271

Reference31 articles.

1. A fourth-order finite-difference method based on non-uniform mesh for a class of singular two-point boundary value problems

2. A general approach to approximate solutions of nonlinear differential equations using particle swarm optimization

3. Multiobjective structural optimization using a microgenetic algorithm

4. An application of swarm optimization to nonlinear programming

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On the Formulation of Metaheuristic Algorithm-Based Approximation Approach for Nonlinear Ordinary Differential Equations with Application to Heat Exchanger Problem;Pertanika Journal of Science and Technology;2020-10-21

2. Design of neuro-evolutionary model for solving nonlinear singularly perturbed boundary value problems;Applied Soft Computing;2018-01

3. Intelligent computing for Mathieu’s systems for parameter excitation, vertically driven pendulum and dusty plasma models;Applied Soft Computing;2018-01

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