Special Issue: New trends by Discrete Fractional Operators with Numerical and Neural Networking Techniques

Overview

Discrete fractional calculus has arisen as a dynamic mathematical tool for expressing memory, inheritance, and complex dynamic activities that cannot be accurately captured by traditional integer-order models. Incorporation of fractional operators in discrete domains has given new insights into systems illustrated by temporal correlations, non-locality, and multi-scale interactions. This Special Issue aims to highlight advanced advancements in discrete fractional operators and their growing significance in computational science, engineering, and intelligent systems.

 

Fractional-order modeling in discrete frameworks connects theoretical mathematics and real-world applications, offering improved precision in areas such as control systems, signal processing, chaotic dynamics, and data-driven prediction. The development of computational algorithms and neural networking techniques has further enhanced the capacity to simulate, optimize, and interpret discrete fractional systems in both deterministic and stochastic environments.

 

This Special Issue welcomes contributions that investigate analytical, numerical, and intelligent computational techniques for discrete fractional operators. Papers that propose hybrid methodologies relating artificial neural networks (ANNs), deep learning, and soft computing with fractional discrete models are of particular interest. Such studies can cover the way for new paradigms in modeling memory-based systems, increasing accuracy, adaptability, and interpretability in dynamic processes.

 

 

Scope

The scope of this Special Issue includes, but is not limited to, the following themes:

• Novel formulations and generalizations of discrete fractional operators.
• Existence, stability, and convergence analysis of discrete fractional systems.
• Fractional discrete models in physics, biology, finance, and engineering.
• Control and optimization of discrete-time fractional-order systems.
• Fuzzy systems and decision making with neural networking.
• Computational algorithms for solving discrete fractional differential and difference equations.
• Computational analysis of fluid dynamics with neural networking.
• Soliton analysis and nonlinear wave propagation.
• Image processing, detection and sensing.
• Hybrid computational intelligence frameworks combining fractional calculus and machine learning.
• Stability and synchronization in neural network systems with discrete fractional dynamics.

 

 

Goal

Through this Special Issue, we aim to gather involvements that push the boundaries of mathematical theory and computational practice. Importance will be placed on innovation, methodological rigor, and interdisciplinary applications. Researchers from mathematics, computer science, physics, and engineering are encouraged to submit their latest findings.

 

By connecting discrete fractional calculus with modern computational intelligence, this Special Issue pursues to establish a robust platform for exploring how memory-dependent dynamics can be analyzed, predicted, and controlled using advanced mathematical and neural frameworks. The ultimate goal is to strengthen the theoretical foundation while fostering real-world applications in emerging technologies and complex system modeling.

 

 

Guest Editor

Dr. Aziz Khan, akhan@psu.edu.sa

Department of Mathematics and Science,  Prince Sultan University P. O. Box 66833,1586 Riyadh, Saudi Arabia

 

Dr. Usman Younas, usmanalgebra@yahoo.com

Department of Mathematics, Shanghai University, No. 99 Shangda Road, Shanghai 200444, China

 

Dr. Aliya Fahmi,  aliyafahmi@gmail.com

Department of Maths, Faculty of Science, University of Faisalabad, Faisalabad, Pakistan

 

Dr.  Hasib Khan, hkhan@psu.edu.sa

Department of Mathematics and Science, Prince Sultan University P. O. Box 66833, 11586 Riyadh, Saudi Arabia

 

 

Important Dates

Submission Opens: November 10, 2025

Submissions should present original and high-quality research that is not currently under review elsewhere. All manuscripts will undergo a rigorous double-blind peer review process. Previously published conference papers must be substantially extended and clearly identified during submission.

 

 

Submission Information

Submit it online: http://ojs.wiserpub.com/index.php/CM/user/register

Or send it to the email address: flory@universalwiser.com

 

 

Submission Guideline

https://ojs.wiserpub.com/index.php/CM/about/submissions

For any inquiries about this Special Issue, please contact the Editors via flory@universalwiser.com