Journal of Model Based Research
Advancing Quantitative Methods Through Mathematical Modeling
Journal of Model Based Research (JMBR) (ISSN 2643-2811) serves as a premier international platform for advancing mathematical modeling, computational frameworks, and quantitative analysis methodologies. As an open-access, peer-reviewed publication, JMBR bridges theoretical developments with practical implementations across engineering systems, scientific simulation, and computational research domains.
Our journal emphasizes the mathematical foundations, algorithmic innovations, and systematic frameworks that enable researchers to model complex systems, optimize processes, and validate computational approaches. JMBR fosters interdisciplinary collaboration among mathematicians, computer scientists, systems engineers, and computational specialists who develop rigorous quantitative methods.
Through transparent peer review and rapid publication workflows, JMBR accelerates the dissemination of methodological breakthroughs that advance modeling science and computational research capabilities worldwide.
Peer-reviewed validation of computational frameworks and algorithmic innovations
Streamlined review process with average 21-day submission-to-first-decision timeline and 5-day acceptance-to-publication turnaround
Global dissemination ensures broad impact for methodological advances
JMBR publishes original research that advances mathematical modeling theory, develops novel computational algorithms, and establishes robust quantitative frameworks. Our editorial priorities emphasize methodological innovation, mathematical validation, and reproducible computational science.
Core Research Domains
JMBR welcomes contributions that strengthen the mathematical and computational foundations of modeling research. Manuscripts should demonstrate rigorous methodology, algorithmic novelty, or significant advances in quantitative frameworks.
Differential equations, stochastic processes, optimization theory, and analytical frameworks
Computational algorithms, numerical methods, convergence analysis, and complexity evaluation
Discrete-event simulation, Monte Carlo methods, agent-based models, and system dynamics
Control theory, state-space models, feedback systems, and stability analysis
Requirements modeling, functional specification, architectural frameworks, and verification methods
Unified Modeling Language, Petri nets, block diagrams, and visual specification languages
Meta-modeling, model transformation, code generation, and domain-specific languages
Software architectures, middleware platforms, computational toolkits, and integration methodologies
Hardware-in-the-loop testing, real-time operating systems, and latency optimization
Regression analysis, Bayesian inference, multivariate statistics, and experimental design
Linear/nonlinear programming, heuristic algorithms, metaheuristics, and constraint satisfaction
Ontologies, semantic models, knowledge representation, and abstraction frameworks
Original methodological contributions presenting novel mathematical models, algorithms, or computational frameworks with rigorous validation
Detailed development and validation of new quantitative techniques, modeling approaches, or computational tools
Innovative algorithmic designs, complexity analysis, and performance optimization in computational modeling
Comprehensive, structured reviews synthesizing evidence across modeling studies with methodological rigor
Authoritative surveys of mathematical modeling domains, algorithmic landscapes, or computational paradigms with critical synthesis
Concise reports of significant findings that merit rapid publication
Brief communications on algorithmic refinements, computational optimizations, or methodological observations
Comparative analyses of modeling frameworks, algorithmic performance evaluations, or computational efficiency assessments
Detailed documentation of datasets generated through modeling processes, emphasizing reusability and transparency
Descriptions of novel software implementations, modeling tools, or computational platforms with scientific impact
In-depth analyses of real-world modeling applications demonstrating methodological innovation
Expert insights on emerging modeling paradigms, research priorities, or methodological debates in quantitative science
Thought-provoking articles expressing scholarly viewpoints on trends, challenges, or future directions in modeling research
Concise correspondence addressing previously published work or current issues in the modeling community
JMBR maintains partnerships with leading research institutions worldwide, fostering collaboration in mathematical modeling and computational science. Our author community spans universities, research laboratories, and technology institutes across multiple continents. With a 54% acceptance rate and an average submission-to-publication time of 45 days, JMBR provides an efficient, rigorous pathway for disseminating high-quality modeling research.
- Technische Universität München View Research
- University of Hildesheim View Research
- Hubei University of Technology View Research
- Yangtze University View Research
- Institute of Management & Research (IMR), India View Research
- Institute of Management & Science (IMS), India View Research
- G.H. Raisoni Institute of Business Management, India View Research
Submit Your Research to JMBR
Join our international community of computational researchers advancing mathematical modeling and quantitative methods. With a 54% acceptance rate and average 21-day first decision time, JMBR offers a rapid, rigorous publication pathway. Submit your work today and reach a global audience within weeks of acceptance.
Editorial Inquiries
For questions regarding scope alignment, submission guidelines, or editorial policies, contact our team at [email protected]
