COMPUTERS & MATHEMATICS WITH APPLICATIONS

Scope & Guideline

Bridging Theory and Application in Mathematics

Introduction

Welcome to your portal for understanding COMPUTERS & MATHEMATICS WITH APPLICATIONS, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN0898-1221
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 1975 to 2024
AbbreviationCOMPUT MATH APPL / Comput. Math. Appl.
Frequency24 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND

Aims and Scopes

The journal 'Computers & Mathematics with Applications' focuses on the intersection of computational methods and mathematical applications across various fields. It aims to disseminate high-quality research that bridges theory and practice, particularly in numerical analysis, computational modeling, and simulation techniques.
  1. Numerical Methods and Algorithms:
    The journal emphasizes the development and application of numerical methods for solving mathematical problems, particularly those arising in physics and engineering.
  2. Computational Modeling:
    It covers a wide range of computational models, including fluid dynamics, heat transfer, and biological systems, emphasizing their mathematical foundations and practical implementations.
  3. Error Analysis and Stability:
    Papers often focus on the stability and error analysis of numerical methods, providing rigorous assessments of various computational techniques.
  4. Adaptive and Multiscale Methods:
    The journal features research on adaptive methods and multiscale approaches that improve computational efficiency and accuracy for complex problems.
  5. Interdisciplinary Applications:
    Research published in the journal spans multiple disciplines, including materials science, environmental engineering, and biomedical applications, showcasing the versatility of computational mathematics.
The journal is currently experiencing growth in several research themes that reflect the latest advancements in computational mathematics and its applications. These emerging trends indicate a shift towards more innovative methodologies and interdisciplinary approaches.
  1. Physics-Informed Neural Networks (PINNs):
    The integration of machine learning techniques, particularly physics-informed neural networks, is gaining traction for solving partial differential equations, showcasing the convergence of traditional methods with modern computational intelligence.
  2. Adaptive Mesh Methods:
    Adaptive mesh methods are increasingly popular, emphasizing the need for efficient computational techniques that can handle complex geometries and varying solution characteristics.
  3. Multiscale and Multiphysics Approaches:
    There is a growing emphasis on multiscale and multiphysics modeling, which allows for the simulation of complex systems that involve interactions across different scales and physical phenomena.
  4. Data-Driven Methods:
    Research focusing on data-driven modeling and simulation techniques is on the rise, reflecting the increasing availability of data and the need for computational methods that can leverage this information effectively.
  5. Hybrid Computational Techniques:
    Hybrid methods that combine different numerical approaches are emerging, allowing for enhanced flexibility and accuracy in solving challenging mathematical problems.

Declining or Waning

While 'Computers & Mathematics with Applications' continues to thrive in many areas, certain themes are witnessing a decline in prominence. This may reflect shifts in research focus or the emergence of new methodologies and technologies.
  1. Traditional Finite Element Methods:
    There seems to be a waning interest in traditional finite element methods, as researchers increasingly explore hybrid and virtual element methods that provide greater flexibility and efficiency.
  2. Basic Computational Techniques:
    Basic computational techniques are less frequently reported, indicating a shift towards more complex and sophisticated algorithms and methods that address contemporary challenges.
  3. Static Problem Formulations:
    Research focusing solely on static problem formulations is declining as the field moves towards dynamic and time-dependent problems that better reflect real-world scenarios.

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