Mathematical Modeling and Methods for Industrial Applications : 1st ICoIAM, Hammamet, Tunisia, December 19-21, 2025 (Springer Proceedings in Mathematics & Statistics)

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Mathematical Modeling and Methods for Industrial Applications : 1st ICoIAM, Hammamet, Tunisia, December 19-21, 2025 (Springer Proceedings in Mathematics & Statistics)

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Full Description

This book brings together selected, peer‑reviewed contributions presented at the First International Conference of Industrial and Applied Mathematics (ICoIAM), held in Hammamet, Tunisia, from 19 to 21 December 2025. The works in this volume showcase recent advances in applied and industrial mathematics, with particular emphasis on fractional calculus and dynamical systems, partial differential equations, optimization, statistical modelling, and computational methods. These contributions illustrate how modern mathematical ideas enable solutions to real‑world problems in engineering, physics, information and communication technologies, and the life sciences.

In its first edition, the ICoIAM conference gathered researchers from North Africa, Europe, the Middle East, and other regions around the world. It was conceived as a specialized platform for researchers working in mathematical modelling, optimization, and industrial applications.

Organized by the African Society for Industrial and Applied Mathematics (ASIAM), the conference aims to highlight research activities in these regions and to promote wide-ranging cooperation, both regionally and between senior and early‑career researchers.

 

Contents

New Formula for Divisibility by some prime numbers.- Bright, Dark, Periodic, and Singular Solutions of the Nonlinear Klein-Gordon Equation Using Symbolic and Algebraic Techniques.- Influence of degradation function in phase field brittle fracture model for 2D-polycrystals.- On the distinguishing coloring of some graphs.- On the Diophantine Equation $3^x+10^y=z^2$.- Mathematical Modeling of Nonlinear Current Voltage Characteristics of Photovoltaic Models.- Chaos control in incommensurate fractional discrete neural networks.- Memristor-based Chialvo Neurons Map with Variable Fractional Order: Chaos and Stabilization.- On Iterative Learning Control.- Well-Posedness and Stability of Fractional Thermistor Models with Multi-Order Caputo Derivatives and Nonlocal Joule Heating.- A Mathematical Model and Simulation Framework for Dynamic Sub-band Allocation in IoT Networks.- The geometry of stenosis: Classification of simple axisymmetric stenosis.- Management of DC bus voltage in hybrid system with PV-wind Turbine-battery connected to grid using Twisting sliding mode control.- Stability of Almost-Periodic Solutions of Piecewise Constant Argument Recurrent Neural Networks.- Control of Incommensurate Fractional-Order Discrete-Time SI Model for Computer Viruses.- On Synchronization of Incommensurate Chaotic Fractional Discrete Model of Computer Virus.- Chaotic Dynamics of Discrete-Time Integer- and Fractional-Order Computer Virus Memristor System.- EM-Newton-Raphson Method and Moment-Based Estimation for the Binomial q-Distribution.- Method of Moments Estimation for Continuous q-Distributions.- Global Attractors for the Complex Cahn-Hilliard-Oono Type Equation.- Magnetic, structural properties and morphological evolution of FeTiO2, FeTiO3 nanocomposites synthetized by powder metallurgy process.- Preliminary Validation of the Thermal Hydraulics Module of MOOSE for Research Reactor Applications.- Analysis of a Delay Differential Equation model with Biological application.- Existence of infinitely many solutions for p(x)-Laplacian-like operators with effect of nonlocal terms.- Copula-Based Preprocessing technique for Multi-Label AI Models.- Numerical Analysis of 1D and 2D Pressure-Driven Phase Field Models.- Chaos Generation and Bifurcation Patterns in a Discrete Conformable HIV-Cancer-Immune Model.- On the periodic orbits in certain class of fourth-order autonomous differential equations via averaging theory.- Newton Direction vs. Conjugacy Condition : A Comparative Study of Hybrid Conjugate Gradient Methods.

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