Integrating Elman recurrent neural network with particle swarm optimization algorithms for an improved hybrid training of multidisciplinary datasets-Reference-Cited by-同舟云学术

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Integrating Elman recurrent neural network with particle swarm optimization algorithms for an improved hybrid training of multidisciplinary datasets

Published:2021-11 Issue: Volume:183 Page:115441
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Ab Aziz Mohamad Firdaus,Mostafa Salama A,Mohd. Foozy Cik Feresa,Mohammed Mazin Abed,Elhoseny Mohamed,Abualkishik Abedallah Zaid

Funder

Universiti Tun Hussein Onn Malaysia

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference47 articles.

1. Enhancement of quantum particle swarm optimization in Elman recurrent network with bounded Vmax function;Ab Aziz;Jurnal Teknologi,2016

2. Decision-level fusion scheme for nasopharyngeal carcinoma identification using machine learning techniques;Abd Ghani;Neural Computing and Applications,2020

3. Application of chaos discrete particle swarm optimization algorithm on pavement maintenance scheduling problem;Ahmed;Cluster Computing,2019

4. Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique;Altan;Chaos, Solitons & Fractals,2020

5. A new hybrid model for wind speed forecasting combining long short-term memory neural network, decomposition methods and grey wolf optimizer;Altan;Applied Soft Computing,2021

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