Numerical Mathematics-Theory Methods and Applications

Scope & Guideline

Exploring the Frontiers of Computational Mathematics

Introduction

Delve into the academic richness of Numerical Mathematics-Theory Methods and Applications with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN1004-8979
PublisherGLOBAL SCIENCE PRESS
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 2010 to 2024
AbbreviationNUMER MATH-THEORY ME / Numer. Math.-Theory Methods Appl.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressOffice B, 9/F, Kings Wing Plaza2, No.1 On Kwan St, Shek Mun, NT , Hong Kong 00000, PEOPLES R CHINA

Aims and Scopes

The journal 'Numerical Mathematics: Theory Methods and Applications' focuses on advancing numerical methods and their applications across various fields of mathematics and engineering. It aims to publish high-quality research that enhances the understanding and development of numerical techniques for solving complex mathematical problems.
  1. Numerical Analysis and Error Estimation:
    Research on the accuracy and reliability of numerical methods, including error analysis and convergence assessments for various numerical schemes.
  2. Finite Element and Finite Difference Methods:
    Development and optimization of finite element and finite difference methods for solving partial differential equations (PDEs) and other mathematical models.
  3. Stochastic and Deterministic Methods:
    Exploration of both stochastic and deterministic approaches for solving mathematical problems, particularly in the context of partial differential equations and optimization.
  4. Multiscale and Nonlocal Models:
    Investigation of numerical methods for multiscale and nonlocal models, addressing complex phenomena that require innovative computational approaches.
  5. Applications in Engineering and Physics:
    Application of numerical methods to real-world problems in engineering, physics, and other applied sciences, showcasing their practical relevance.
  6. Innovative Computational Techniques:
    Introduction of novel computational techniques, including machine learning and adaptive algorithms, to enhance numerical simulations.
The journal is currently witnessing several emerging themes that reflect the evolving landscape of numerical mathematics. These trends indicate a shift towards more innovative and interdisciplinary approaches.
  1. Machine Learning and Data-Driven Methods:
    There is a growing trend towards integrating machine learning techniques into numerical methods, particularly for solving PDEs and optimization problems, highlighting the relevance of data-driven approaches in modern mathematics.
  2. Fractional Calculus and Nonlocal Models:
    An increasing focus on fractional calculus and nonlocal models reflects the rising interest in capturing complex dynamics that traditional models may not adequately address.
  3. Adaptive and Efficient Algorithms:
    Emerging themes include the development of adaptive algorithms that enhance computational efficiency and accuracy, particularly in high-dimensional and complex problems.
  4. Interdisciplinary Applications:
    There is a notable increase in research applying numerical methods to interdisciplinary fields, such as finance, biology, and materials science, demonstrating the versatility of numerical techniques in addressing diverse challenges.
  5. Advanced Error Analysis Techniques:
    Recent publications show a trend towards sophisticated error analysis techniques that provide deeper insights into the performance of numerical methods, furthering the understanding of their reliability.

Declining or Waning

While the journal has consistently focused on various numerical methods, some themes have shown a decline in prominence in recent years. These waning scopes reflect shifts in research interests or advancements in alternative methodologies.
  1. Traditional Numerical Techniques:
    There has been a noticeable decrease in the publication of papers focusing on classical numerical methods, such as basic finite difference and finite element techniques, with more emphasis shifting towards advanced and hybrid methodologies.
  2. Low-Dimensional Analysis:
    Research on low-dimensional numerical models is becoming less frequent, as researchers increasingly explore higher-dimensional problems and complex systems that require more sophisticated approaches.
  3. Purely Theoretical Studies:
    Theoretical studies without practical applications are declining, as the journal increasingly favors papers that demonstrate the applicability of numerical methods to real-world scenarios.

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