An Efficient Stochastic Numerical Computing Framework for the Nonlinear Higher Order Singular Models

An Efficient Stochastic Numerical Computing Framework for the Nonlinear Higher Order Singular Models

The focus of the present study is to present a stochastic numerical computing framework based on Gudermannian neural networks (GNNs) together with the global and local search genetic algorithm (GA) and active-set approach (ASA), i.e., GNNs-GA-ASA. The designed computing framework GNNs-GA-ASA is test...

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Bibliographic Details
Main Authors: Zulqurnain Sabir, Hafiz Abdul Wahab, Shumaila Javeed, Haci Mehmet Baskonus
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Fractal and Fractional
Subjects:
gudermannian neural network
higher order
singular
genetic algorithms
statistical analysis
active-set approach
Online Access:https://www.mdpi.com/2504-3110/5/4/176

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