Nonlinear Analysis-Modelling and Control

Scope & Guideline

Advancing nonlinear insights for a transformative future.

Introduction

Welcome to the Nonlinear Analysis-Modelling and Control information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of Nonlinear Analysis-Modelling and Control, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN1392-5113
PublisherVILNIUS UNIV, INST MATHEMATICS & INFORMATICS
Support Open AccessYes
CountryLithuania
TypeJournal
Convergefrom 2009 to 2024
AbbreviationNONLINEAR ANAL-MODEL / Nonlinear Anal.-Model Control
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressAKADEMIJOS 4, VILNIUS 08663, LITHUANIA

Aims and Scopes

The journal 'Nonlinear Analysis-Modelling and Control' is dedicated to the exploration of nonlinear phenomena through mathematical modeling and analysis. It focuses on the development and application of advanced mathematical methods to solve complex problems across various fields, including differential equations, control theory, and systems dynamics.
  1. Nonlinear Differential Equations:
    The journal emphasizes the study of nonlinear differential equations, including fractional and impulsive systems, employing various analytical and numerical techniques.
  2. Mathematical Modeling:
    It promotes research that involves the formulation and analysis of mathematical models to describe real-world phenomena, particularly in biology, ecology, and engineering.
  3. Control Theory:
    A significant focus is on control systems, particularly optimal control, synchronization, and stability analysis of nonlinear systems.
  4. Fractional Calculus:
    The journal publishes studies involving fractional calculus, exploring its applications in modeling dynamic processes and systems.
  5. Fixed Point Theory:
    Research related to fixed point theorems and their applications in solving differential equations, particularly in the context of nonlinear mappings.
Recent publications in 'Nonlinear Analysis-Modelling and Control' indicate several emerging themes that reflect current trends in mathematical modeling and analysis.
  1. Fractional Dynamics:
    There is a growing trend in the exploration of fractional dynamics, particularly in modeling complex systems in biology and physics, indicating an increasing interest in fractional derivatives and integrals.
  2. Stochastic Systems and Noise Analysis:
    Research focused on stochastic systems, including noise impacts on nonlinear dynamics, is becoming more prominent, reflecting the need to incorporate randomness in modeling.
  3. Epidemiological Modeling:
    A significant increase in the publication of epidemiological models, particularly in light of recent global health crises, demonstrates the journal's responsiveness to current events.
  4. Synchronization in Complex Networks:
    Emerging studies are increasingly addressing synchronization phenomena in complex networks, highlighting applications in neural networks and multi-agent systems.
  5. Computational Techniques and Simulations:
    There is a notable rise in the use of computational methods and simulations to analyze and solve complex mathematical models, showcasing an integration of numerical analysis with theoretical approaches.

Declining or Waning

While the journal has consistently focused on various mathematical and control-related themes, certain areas appear to be declining in prominence based on recent publications.
  1. Classical Linear Systems:
    There has been a noticeable decrease in the publication of research focused on classical linear systems, with a shift towards more complex nonlinear and fractional systems.
  2. Traditional Control Techniques:
    Interest in traditional control techniques is waning, as newer methodologies involving fractional-order and adaptive control strategies become more prevalent.
  3. Static Mathematical Models:
    The journal has seen a decline in the use of static models, with more emphasis now placed on dynamic systems and their time-dependent behaviors.
  4. Elementary Mathematical Analysis:
    There appears to be a reduced focus on basic mathematical analysis topics, as the journal increasingly prioritizes advanced techniques and interdisciplinary applications.

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