Journal of Applied Mathematics and Computing
Scope & Guideline
Transforming Ideas into Computational Solutions
Introduction
Aims and Scopes
- Mathematical Modelling:
The journal emphasizes the creation and analysis of mathematical models that describe complex phenomena, particularly in fields such as epidemiology, ecology, and engineering. - Numerical Analysis:
A core focus on developing and improving numerical methods for solving differential equations, optimization problems, and integral equations, often involving advanced techniques such as finite element methods and spectral methods. - Control Theory:
Investigating control strategies for dynamic systems, particularly in relation to stochastic processes and systems influenced by delays or perturbations. - Graph Theory and Coding Theory:
Exploring properties of graphs and their applications in coding theory, including the study of various types of codes and their implications for information theory and network design. - Fractional Calculus:
Research into fractional derivatives and their applications in modeling phenomena that exhibit memory and hereditary properties, including applications in physics and engineering.
Trending and Emerging
- Epidemiological Modeling:
Significant attention is being given to mathematical models that address infectious diseases, particularly in light of the COVID-19 pandemic, focusing on dynamics, control strategies, and vaccination impacts. - Stochastic Systems and Uncertainty Quantification:
An increasing number of papers are focusing on stochastic models that incorporate uncertainty, reflecting a growing interest in how randomness affects system dynamics. - Fractional Differential Equations:
Research into fractional calculus has gained momentum, especially in modeling processes with memory effects, highlighting its applicability across various scientific domains. - Advanced Numerical Methods:
Emerging trends include the development of high-order numerical methods and adaptive algorithms that improve accuracy and efficiency in computational solutions. - Multi-criteria Decision Making and Fuzzy Logic:
There is a rise in research involving fuzzy logic and multi-criteria decision-making frameworks, emphasizing their relevance in complex decision environments.
Declining or Waning
- Traditional Optimization Techniques:
There has been a shift away from classical optimization methods in favor of more advanced techniques that incorporate elements of machine learning and adaptive algorithms. - Basic Graph Theory:
Basic graph theory topics have become less prominent, with a noticeable trend towards more complex structures and applications, such as fuzzy graphs and quantum codes. - Static Mathematical Models:
There is a decreasing emphasis on static models that do not account for dynamics or time-varying parameters, as the trend moves towards dynamic modeling that incorporates temporal changes.
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