Eurasian Journal of Mathematical and Computer Applications

Scope & Guideline

Fostering Interdisciplinary Insights in Mathematical Applications.

Introduction

Explore the comprehensive scope of Eurasian Journal of Mathematical and Computer Applications through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Eurasian Journal of Mathematical and Computer Applications in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN2306-6172
PublisherL N GUMILYOV EURASIAN NATL UNIV
Support Open AccessNo
CountryKazakhstan
TypeJournal
Convergefrom 2013 to 2024
AbbreviationEURASIAN J MATH COMP / Eurasian J. Math. Comput. Appl.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressPUSHKIN ST, 11, RM 210, ASTANA 010008, KAZAKHSTAN

Aims and Scopes

The Eurasian Journal of Mathematical and Computer Applications focuses on the diverse applications of mathematical methods and computational techniques across various scientific and engineering domains. The journal aims to publish high-quality research that contributes to the theoretical foundations and practical implementations of mathematical and computational models.
  1. Mathematical Modeling:
    The journal emphasizes the development and application of mathematical models to solve real-world problems across various fields, including physics, engineering, and environmental science.
  2. Computational Techniques:
    A significant focus is placed on advanced computational methods, including numerical simulations, algorithm design, and optimization techniques for solving complex mathematical problems.
  3. Inverse Problems:
    The journal frequently publishes research addressing inverse problems, which involve determining unknown parameters or inputs from observed data, a crucial aspect in various scientific disciplines.
  4. Machine Learning and Data Analysis:
    There is a growing interest in integrating machine learning techniques with mathematical modeling and data analysis, particularly in applications related to big data and smart cities.
  5. Interdisciplinary Research:
    The journal supports interdisciplinary research that connects mathematical applications with areas such as biology, economics, and environmental science, fostering collaboration across disciplines.
The Eurasian Journal of Mathematical and Computer Applications has witnessed a rise in specific themes and methodologies in recent publications. These emerging scopes reflect the evolving landscape of research priorities and the integration of new technologies.
  1. Big Data and Smart Cities:
    There is a notable increase in research utilizing big data analytics and machine learning for urban management and smart city applications, highlighting the relevance of mathematical modeling in contemporary societal challenges.
  2. Inverse and Ill-Posed Problems:
    An emerging trend in the journal is the focus on inverse and ill-posed problems, which require sophisticated mathematical techniques and have significant implications in fields like medical imaging and geophysics.
  3. Neural Networks and Artificial Intelligence:
    The integration of neural networks and AI methodologies into mathematical modeling and computational techniques is on the rise, indicating a shift towards more adaptive and intelligent systems in various applications.
  4. Environmental and Ecological Modeling:
    Research on environmental issues, including climate modeling and ecological simulations, has gained traction, reflecting an increased awareness of the importance of mathematical applications in addressing global challenges.
  5. Fractional Calculus and Nonlocal Problems:
    There is a growing interest in the study of fractional calculus and nonlocal problems, which provide new insights and solutions to complex systems, showcasing the journal's commitment to advancing mathematical theory.

Declining or Waning

While the journal continues to publish a wide range of topics, certain areas of research have seen a decline in focus over recent years. These waning themes indicate shifting priorities and emerging interests within the academic community.
  1. Conventional Statistical Methods:
    There appears to be a decreasing emphasis on traditional statistical methods in favor of more advanced computational techniques and machine learning approaches, reflecting a broader trend towards data-driven analysis.
  2. Basic Theoretical Studies:
    Research papers focusing solely on theoretical aspects without practical applications have become less frequent, as the journal increasingly favors studies that demonstrate real-world applicability of mathematical concepts.
  3. Single-Domain Applications:
    The focus on research limited to a single domain without interdisciplinary connections is waning, as there is a growing demand for studies that integrate multiple fields and showcase collaborative efforts.

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