Mathematical Modeling and Algorithm Application (MMAA)
Mathematical Modeling and Algorithm Application (MMAA) is a peer-reviewed journal published by Darcy & Roy Press. The mission of the journal is to provide an academic forum for discussing the issues of mathematical modeling, algorithm application, theoretical and applied mathematics across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Aims & Scope
Mathematical Modeling and Algorithm Application (MMAA) is a peer-reviewed journal published by Darcy & Roy Press. The mission of the journal is to provide an academic forum for discussing the issues of mathematical modeling, algorithm application, theoretical and applied mathematics across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Aims
- To provide a global peer-reviewed academic forum for mathematicians, engineering researchers and industry practitioners to share innovative theories, modeling methods and practical findings on mathematical modeling, algorithm and applied mathematics.
- To facilitate worldwide academic exchange and interdisciplinary cooperation among scholars focusing on pure mathematics, modeling optimization and practical algorithm implementation across diverse industrial fields.
- To bridge theoretical mathematical research and real-world industrial application, promoting the transformation of mathematical modeling and algorithm achievements into practical solutions for engineering and social economic problems.
- To encourage in-depth innovative research on emerging algorithm trends, modeling hot topics and practical mathematical challenges in global theoretical and applied mathematics domains.
Scope
The journal covers a wide range of topics related to mathematical modeling and algorithm application, including but not limited to:
Theoretical Mathematics & Mathematical Modeling
- Fundamental mathematical theory, including algebra, mathematical analysis, probability theory and mathematical statistics foundation
- Continuous and discrete mathematical modeling, including dynamic system modeling, stochastic modeling and optimization mathematical modeling
- Mathematical optimization theory, including convex optimization, integer programming and multi-objective optimization modeling methods
- Computational mathematical theory, including numerical analysis, finite element theory and approximate calculation modeling technology
Algorithm Design & Cross-field Applied Mathematics
- Intelligent algorithm research, including machine learning algorithms, heuristic optimization algorithms and deep learning modeling algorithms
- Engineering applied algorithms, including industrial numerical algorithms, signal processing algorithms and mechanical simulation mathematical algorithms
- Data-driven modeling application, including big data mining algorithms, statistical modeling and industrial data prediction modeling
- Economic and social mathematical application, including econometric modeling, operational research algorithm and social system mathematical simulation