Aims & Scope
Journal of Model-Based Research publishes rigorous quantitative research advancing mathematical modeling, computational algorithms, and simulation methodologies across scientific and engineering domains.
Research Scope
Mathematical & Computational Modeling
- Theoretical frameworks for model development
- Algorithm design and optimization
- Numerical methods and computational techniques
- Predictive modeling and forecasting systems
- Stochastic and deterministic modeling approaches
- Multi-scale and multi-physics simulations
"A novel finite element algorithm for solving nonlinear partial differential equations in fluid dynamics with adaptive mesh refinement."
Systems Modeling & Control Theory
- Dynamic systems modeling and analysis
- Control system design and optimization
- Feedback mechanisms and stability analysis
- Cyber-physical systems modeling
- Model-based controller development
- Real-time simulation and hardware-in-the-loop testing
"Model predictive control framework for autonomous vehicle trajectory optimization using receding horizon techniques."
Data-Driven Modeling & Machine Learning
- Statistical modeling and inference methods
- Machine learning algorithm development
- Deep learning architectures for modeling tasks
- Reinforcement learning and adaptive systems
- Data assimilation and model calibration
- Computational intelligence methods
"Physics-informed neural networks for solving inverse problems in computational mechanics with uncertainty quantification."
Scientific & Engineering Applications
- Molecular dynamics and computational chemistry
- Materials science modeling and simulation
- Environmental and climate modeling systems
- Computational fluid dynamics and mechanics
- Energy systems modeling and optimization
- Aerospace and automotive engineering models
"Molecular dynamics simulation framework for predicting protein-ligand binding affinities using enhanced sampling techniques."
Graphical & Visual Modeling
Model-based design methodologies, visual programming frameworks, simulation visualization techniques, and graphical model representation systems.
Operations Research & Optimization
Mathematical optimization algorithms, linear and nonlinear programming, discrete event simulation, and decision support systems.
Financial & Economic Modeling
Quantitative risk assessment models, market forecasting algorithms, econometric modeling techniques, and computational finance methods.
Agent-Based & Network Modeling
Multi-agent system simulations, network dynamics modeling, complex adaptive systems, and emergent behavior analysis frameworks.
Model Verification & Validation
Validation methodologies, uncertainty quantification techniques, sensitivity analysis frameworks, and model credibility assessment.
High-Performance Computing
Parallel computing algorithms, distributed simulation frameworks, GPU-accelerated modeling, and scalable computational methods.
Quantum Computing Models
Quantum algorithm development, quantum simulation frameworks, and hybrid classical-quantum computational methods.
Neuromorphic Computing
Brain-inspired computational models, spiking neural networks, and biologically-plausible learning algorithms.
Digital Twin Technologies
Virtual replica modeling frameworks, real-time synchronization algorithms, and predictive maintenance systems (methodology focus only).
Explainable AI Models
Interpretable machine learning frameworks, model transparency techniques, and algorithmic accountability methods.
Clinical Outcomes & Patient Care Research
Rationale: Studies focused on clinical decision-making, treatment effectiveness, patient outcomes, or healthcare delivery fall outside our quantitative methods focus. Disease progression models are acceptable only when emphasizing mathematical/computational methodology development.
Purely Empirical Studies Without Modeling
Rationale: Observational studies, experimental results, or data analyses without substantial model development, algorithm innovation, or computational framework contribution do not align with our scope.
Software Implementation Reports
Rationale: Descriptions of software tools, user interfaces, or application implementations without novel algorithmic or methodological contributions are not considered. Focus must be on underlying computational methods.
Qualitative Social Science Research
Rationale: Qualitative studies, policy analyses, or social science research without quantitative modeling components fall outside our technical scope. Computational social science with strong modeling focus may be considered.
Review Articles Without Methodological Synthesis
Rationale: Literature reviews or surveys that summarize existing work without providing methodological synthesis, comparative analysis frameworks, or novel taxonomies are not prioritized.
Article Types & Priorities
Fast-Track Review
Standard Review
Selective Acceptance
Editorial Standards
Reporting Guidelines
Adherence to discipline-specific standards: CONSORT for trials, PRISMA for reviews, ARRIVE for animal studies, EQUATOR network guidelines.
Data Availability
Code and data sharing required for computational studies. Repositories: GitHub, Zenodo, Figshare. Proprietary data must include access protocols.
Ethics & Compliance
IRB approval for human subjects, IACUC for animal research, institutional approval for sensitive data. Declaration of conflicts of interest mandatory.
Preprint Policy
Preprints on arXiv, bioRxiv, or similar servers accepted. Must be declared at submission. Does not affect consideration for publication.
Ready to Submit?
Ensure your manuscript focuses on quantitative methods, computational frameworks, or mathematical modeling innovations. Review our author guidelines for formatting and submission requirements.
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