Recurrent Neural Networks, Bifurcation Analysis and Control Theory of Complex Systems :: Special Issue

Applied and Computational Mathematics

ISSN Online: 2328-5613; ISSN Print: 2328-5605

Frequency: 4 issues per year

DOI: 10.11648/j.acm

Website: http://www.science-discovery.org/journal/acm

Submit an Article

Submit an Abstract

Time to first decision

1-2 weeks
First decision to acceptance

4-6 weeks
Acceptance to publication

1-2 weeks

Special Issue

Recurrent Neural Networks, Bifurcation Analysis and Control Theory of Complex Systems

Submission Deadline: 20 February 2018
Status: Submission Closed
Lead Guest Editor: Adnène Arbi

About This Special Issue

In the last few years, several systems of neural networks have been investigated in nonlinear systems theory and have had a huge impact on the scientist research. Due to their complexities in the design, analysis, and control, innovative ideas, novel models, and techniques are still expected in the future in these expanding areas.

This special issue is intended to present and discuss modeling in recurrent neural networks and their complexity in the nonlinear systems theory. It is expected that novel complex models, their bifurcation analysis, and their related control techniques will be established. Among others, applications in pattern recognition, optimization, cryptography and biosciences disciplines are especially encouraged to be submitted to this special issue to present their related latest developments.

Lead Guest Editor

Adnène Arbi

Laboratory of Engineering Mathematics (LR01ES13), Tunisia Polytechnic School, University of Carthage, Bizerta, Tunisia

Guest Editors

Arturo Tozzi

Department of Physics, University of North Texas, Texas, United States
James F Peters

Department of Electrical and Computer Engineering, University of Manitoba, Manitoba, Canada
Ruan Yongxiang

Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, United States
Aydin Azizi

Department of engineering, German University of Technology, Muscat, Oman
Yinyan Zhang

Department of Computing, The Hong Kong Polytechnic University, Hum Hom, Hong Kong
Komeil Raisian

Research Center for Software Technology and Management (Softam), Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Kajang, Malaysia
Komeil Raisan

School of Computer Science, National University of Malaysia, Selangor, Malaysia
Zhinan Xia

Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, China
Alpana Upadhyay

Department of Master of Computer Applications, Sunshine College, Gujarat Technological University, Rajkot, India
Jridi Ichraf

Quantitative Methods Department, Faculty of Economics and Management of Sfax, Sfax, Tunisia
Nitin Shelke

Department of Computer Science & Engineering, G. H. Raisoni college of Engineering and Management, Amravati, India
Mehdi Fallah

Renewable Energy Research Center (RERC), Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran
Prof. Dr. Hamed Daei Kasmaei

Department of Applied Mathematics and Computer Science, Islamic Azad University,Central Tehran Branch, Tehran, Iran, Tehran, Iran
Elham Ahmadi

Department of Mathematics, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran

Published Articles

Analysis of Computer Virus Propagation Based on Compartmental Model

Pabel Shahrear , Amit Kumar Chakraborty , Md. Anowarul Islam , Ummey Habiba

Issue: Volume 7, Issue 1-2, January 2018

Pages: 12-21

Received: 25 June 2017

Accepted: 16 August 2017

Published: 6 September 2017

DOI: 10.11648/j.acm.s.2018070102.12

Downloads:

Views:

Abstract: Computer viruses pose a considerable problem for users of personal computers. In order to effectively defend against a virus, this paper proposes a compartmental model SAEIQRS (Susceptible – Antidotal – Exposed - Infected – Quarantine - Recovered - Susceptible) of virus transmission in a computer network. The differential transformation method (DTM... Show More

Download PDF

View Online
Bifurcation Behaviour and Stability Analysis of a Nano-Beam Subjected to Electrostatic Pressure

Aydin Azizi , Niloofar Malekzadeh Fard , Hamed Mobki , Adnène Arbi

Issue: Volume 7, Issue 1-2, January 2018

Pages: 1-11

Received: 16 June 2017

Accepted: 19 June 2017

Published: 11 July 2017

DOI: 10.11648/j.acm.s.2018070102.11

Downloads:

Views:

Abstract: This paper deals with the study of bifurcation behavior of a capacitive nano-beam considering electrostatic, Casimir and van der Waals forces. A modified mass-spring model has been implemented for analysis of the nano-beam behavior. The model has been adjusted and corrected with Euler-Bernoulli beam model, because of its less accuracy compared to d... Show More

Download PDF

View Online