Journal of Applied Mathematics Statistics and Informatics

Scope & Guideline

Advancing Knowledge in Applied Mathematics and Statistics

Introduction

Welcome to your portal for understanding Journal of Applied Mathematics Statistics and Informatics, 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
ISSN1336-9180
PublisherSCIENDO
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationJ APPL MATH STAT INF / J. Appl. Math. Stat. Inform.
Frequency2 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressBOGUMILA ZUGA 32A, WARSAW, MAZOVIA 01-811, POLAND

Aims and Scopes

The Journal of Applied Mathematics Statistics and Informatics focuses on the intersection of mathematics, statistics, and computational methodologies to address practical problems across various domains. The journal emphasizes innovative applications of mathematical theories and statistical techniques in fields such as finance, engineering, healthcare, and information technology.
  1. Mathematical Modeling and Optimization:
    The journal explores various mathematical modeling techniques and optimization methods, including hybrid algorithms, to solve real-world problems in fields like finance and economics.
  2. Statistical Analysis and Risk Assessment:
    Research in this area includes advanced statistical methods for analyzing data, particularly in risk assessment scenarios like credit risk and survival analysis in healthcare.
  3. Computational Techniques and Algorithms:
    Focus on developing and applying computational algorithms for data processing, image analysis, and performance evaluation in systems, showcasing the integration of computational mathematics.
  4. Fuzzy Logic and Intuitionistic Fuzzy Sets:
    The journal includes studies on fuzzy logic applications, particularly in graph theory and clustering, highlighting the relevance of fuzzy sets in decision-making processes.
  5. Distribution Theory and Its Applications:
    Research on new distributions, their properties, and applications across various domains, aiming to enhance statistical modeling techniques.
The journal has shown a dynamic evolution in its research themes, with several emerging areas gaining traction in recent years. These trends indicate the journal's responsiveness to contemporary challenges and advancements in mathematics and statistics.
  1. Hybrid Computational Methods:
    There is an increasing interest in hybrid methods that combine different algorithms, such as conjugate gradient methods in optimization, reflecting the demand for more efficient computational techniques.
  2. Machine Learning and Data Science Applications:
    The application of machine learning techniques in statistical analysis and economic modeling is trending, showcasing the journal's alignment with current data-driven research trends.
  3. Healthcare Data Analysis:
    Emerging themes related to survival analysis and cancer data demonstrate the journal's commitment to addressing pressing healthcare issues through statistical methodologies.
  4. Fuzzy and Intuitionistic Approaches:
    A growing focus on fuzzy logic and intuitionistic fuzzy sets indicates a trend towards more nuanced approaches to uncertainty and decision-making in complex systems.
  5. Complex Systems and Network Analysis:
    Recent publications highlight the exploration of complex systems, including graph theory and network dynamics, indicating an emerging interest in understanding interconnected systems.

Declining or Waning

While the journal has maintained a robust focus on several core areas, certain themes appear to be declining in prominence based on recent publication trends. These waning scopes may reflect shifts in research priorities or emerging methodologies.
  1. Classical Statistical Methods:
    There seems to be a decline in papers focusing on traditional statistical techniques, as the journal increasingly emphasizes modern computational methods and novel statistical models.
  2. Pure Theoretical Mathematics:
    Research that is purely theoretical without practical application is becoming less frequent, indicating a shift towards applied mathematics that directly addresses real-world issues.
  3. Single-Domain Focus Studies:
    There is a noticeable reduction in studies that focus exclusively on a single mathematical or statistical domain, as interdisciplinary approaches gain more traction in the journal's publications.

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