Computational and Applied Mathematics investigates computational costs and dynamical behavior in stochastic systems, including stick-slip phenomena. It also explores physics-informed machine learning for solving differential and integral equations, and fuzzy rule-based systems for decision-making and prediction. The journal further examines sub-diffusive fractional differential equations, gradient-based optimization methods for large-scale problems, and the convergence of numerical methods for stochastic differential equations.
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Publication & Citation Trend
Articles published
Times cited
2019
2020
2021
2022
2023
2024
2025
2026
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Applied MathematicsQ2
Computational MathematicsQ2
Subject Classification
Web of Science Categories
Mathematics, Applied
Scopus Categories
Applied MathematicsComputational Mathematics
Research Topics (OpenAlex)
Fractional Differential Equations SolutionsMatrix Theory and AlgorithmsDifferential Equations and Numerical MethodsAdvanced Optimization Algorithms ResearchMulti-Criteria Decision MakingNumerical methods for differential equationsAdvanced Numerical Methods in Computational MathematicsIterative Methods for Nonlinear EquationsOptimization and Variational AnalysisNumerical methods in engineering