AIMS and SCOPE | Computational Mathematics and its Applications

AIMS and SCOPES:

The scope of Computational Mathematics and its Applications covers a wide range of topics in computational mathematics and its applications, including, but not limited to:

Numerical methods and algorithms
Mathematical modeling and simulation
Optimization and control
Computational geometry and topology
Parallel and distributed computing
High-performance computing
Scientific computing
Machine learning and data analytics
Cryptography and security
Computational finance
Computational physics and chemistry
Computational biology and bioinformatics
Image processing and computer vision
Artificial intelligence and robotics

We welcome original research articles, reviews, and short communications that report significant advances in these areas. The journal is also open to publishing articles that demonstrate the application of computational mathematics to real-world problems in various fields such as engineering, physics, finance, and biology.

As an open access journal, Computational Mathematics and its Applications is committed to making research freely available to readers worldwide. The journal charges a publication fee to cover the costs of publishing, but we also offer a waiver for authors from low-income countries or for whom the publication fee is a financial hardship. We adhere to the highest ethical standards in publishing, including the COPE (Committee on Publication Ethics) guidelines, and we encourage authors to follow best practices in research conduct and reporting. We also support data sharing and reproducibility, and we encourage authors to make their data and code available to readers whenever possible.

Overall, Computational Mathematics and its Applications aims to be a valuable resource for researchers, mathematicians, computer scientists, and engineers working in the field of computational mathematics and its applications. We hope that our journal will contribute to advancing knowledge, promoting interdisciplinary research, and solving real-world problems through the use of computational mathematics.

Keywords and sub-topics related to Computational Mathematics and its Applications:

Computational modeling
Mathematical analysis
Stochastic processes
Nonlinear optimization
Scientific visualization
Numerical linear algebra
Finite element analysis
Uncertainty quantification
Machine learning for scientific computing
Computational electromagnetics
Computational fluid dynamics
Numerical weather prediction
High-order methods
Spectral methods
Mesh generation and adaptivity
Topology optimization
Discontinuous Galerkin methods
Multigrid and domain decomposition methods
Meshless methods
Monte Carlo simulations
Time-dependent problems
Inverse problems
Control theory and optimization
Geometric modeling and analysis
Discrete mathematics and combinatorics
Numerical analysis of PDEs
Differential equations and dynamical systems
Mathematical biology
Mathematical finance
Scientific computing software and libraries
Numerical methods for integral equations
Numerical methods for partial differential equations
Numerical methods for ordinary differential equations
Numerical methods for stochastic differential equations
Numerical methods for optimization problems
Computational number theory
Cryptography and information security
Data-driven modeling and simulation
Computational materials science
Computational solid mechanics
Computational acoustics
Wave propagation and scattering
Numerical methods for fluid-structure interaction
Numerical methods for acoustics-structure interaction
Numerical methods for multiphysics problems
Mathematical methods for data analysis and visualization
Big data analytics and machine learning
Numerical methods for signal processing
Computational neuroscience
Numerical methods for shape optimization
Numerical methods for fluid dynamics with complex interfaces
Numerical methods for modeling and simulation of biological systems
Numerical methods for fluid dynamics with moving boundaries
Numerical methods for inverse problems in imaging
Numerical methods for medical imaging
Computational methods for image segmentation and registration
Computational methods for image reconstruction
Numerical methods for subsurface flow and transport
Mathematical methods for finance and risk management
Computational methods for energy systems
Numerical methods for atmospheric and environmental modeling
Numerical methods for ocean modeling
Numerical methods for geophysical fluid dynamics
Computational methods for quantum mechanics
Computational methods for molecular dynamics
Computational methods for chemical reaction engineering
Mathematical methods for geospatial data analysis and visualization
Computational methods for machine learning and data analytics
Numerical methods for optimization of machine learning algorithms
Computational methods for image and speech recognition
Computational methods for natural language processing
Numerical methods for social network analysis
Computational methods for cybersecurity
Numerical methods for transportation systems modeling
Computational methods for smart cities
Computational methods for sustainable development
Numerical methods for decision making under uncertainty
Computational methods for risk assessment and management
Numerical methods for supply chain optimization
Computational methods for manufacturing and logistics
Numerical methods for engineering design optimization
Computational methods for machine design and analysis
Numerical methods for human-centered design
Computational methods for robotics and automation
Numerical methods for control of nonlinear systems
Computational methods for autonomous systems
Numerical methods for distributed systems
Computational methods for cloud computing
Computational methods for edge computing
Numerical methods for internet of things (IoT)
Computational methods for blockchain technology
Numerical methods for virtual and augmented reality
Computational methods for gaming and entertainment
Numerical methods for machine vision and perception
Computational methods for autonomous vehicles
Numerical methods for precision agriculture
Computational methods for bioinformatics
Numerical methods for drug discovery
Computational methods for personalized medicine
Mathematical models and simulations for COVID-19
Computational methods for epidemiology and public health
Numerical methods for environmental monitoring and assessment
Computational methods for renewable energy systems
Numerical methods for smart grid optimization
Computational methods for urban planning and design
Numerical methods for disaster management and mitigation
Computational methods for social media analytics
Numerical methods for sentiment analysis
Computational methods for cybersecurity and digital forensics
Numerical methods for privacy-preserving data analysis
Computational methods for explainable AI
Numerical methods for fairness in machine learning
Computational methods for adaptive systems
Numerical methods for cognitive computing
Computational methods for natural user interfaces
Numerical methods for emotion recognition
Computational methods for virtual assistants and chatbots
Numerical methods for affective computing
Computational methods for e-learning and education
Numerical methods for distance education and telemedicine
Computational methods for cultural heritage preservation
Numerical methods for art and creativity
Computational methods for music and sound synthesis
Numerical methods for language translation and localization
Computational methods for digital humanities
Numerical methods for journalism and media analysis
Computational methods for law and legal reasoning
Numerical methods for public policy analysis
Computational methods for innovation and entrepreneurship
Numerical methods for marketing and advertising
Computational methods for finance and investment
Numerical methods for supply chain management
Computational methods for customer relationship management
Numerical methods for organizational behavior and management
Computational methods for human resources management
Numerical methods for project management
Computational methods for quality control and assurance
Numerical methods for manufacturing and production systems
Computational methods for logistics and transportation systems
Computational methods for service operations management
Numerical methods for revenue management
Computational methods for healthcare management
Numerical methods for sports analytics
Computational methods for smart cities and communities
Numerical methods for sustainable development and environmental management
Computational methods for risk management and insurance
Numerical methods for social network analysis and influence
Computational methods for decision support systems
Computational methods for artificial intelligence and robotics in society
Numerical methods
Mathematical modeling
Scientific computing
Optimization
Data analysis
Machine learning
Artificial intelligence
High-performance computing
Parallel computing
Distributed computing
Monte Carlo methods
Finite element methods
Boundary element methods
Finite difference methods
Spectral methods
Meshless methods
Mesh generation
Grid generation
Adaptive methods
Multiscale methods
Stochastic methods
Uncertainty quantification
Sensitivity analysis
Inverse problems
Nonlinear optimization
Global optimization
Convex optimization
Combinatorial optimization
Linear programming
Nonlinear programming
Integer programming
Mixed-integer programming
Semi-definite programming
Compressed sensing
Sparse optimization
Robust optimization
Multi-objective optimization
Topology optimization
Image processing
Computer vision
Signal processing
Time series analysis
Pattern recognition
Natural language processing
Speech recognition
Speech synthesis
Robotics
Control systems
Nonlinear dynamics
Chaos theory
Fractals
Differential equations
Partial differential equations
Ordinary differential equations
Difference equations
Dynamical systems
Fluid dynamics
Solid mechanics
Electromagnetics
Quantum mechanics
Statistical mechanics
Computational physics
Computational chemistry
Computational biology
Computational neuroscience
Computational finance
Computational social science
Computational linguistics
Computational journalism
Computational law
Computational economics
Computational engineering
Computational geosciences
Computational fluid dynamics
Computational electromagnetics
Computational acoustics
Computational elasticity
Computational materials science
Computational nanoscience
Computational surface science
Computational tribology
Computational plasma physics
Computational astrophysics
Computational cosmology
Computational ecology
Computational geology
Computational meteorology
Computational oceanography
Computational psychology
Computational methods for edge computing
Numerical methods for internet of things (IoT)
Computational methods for blockchain technology
Numerical methods for virtual and augmented reality
Computational methods for gaming and entertainment
Numerical methods for machine vision and perception
Computational methods for autonomous vehicles
Numerical methods for precision agriculture
Computational methods for bioinformatics
Numerical methods for drug discovery
Computational methods for personalized medicine
Mathematical models and simulations for COVID-19
Computational methods for epidemiology and public health
Numerical methods for environmental monitoring and assessment
Computational methods for renewable energy systems
Numerical methods for smart grid optimization
Computational methods for urban planning and design
Numerical methods for disaster management and mitigation
Computational methods for social media analytics
Numerical methods for sentiment analysis
Computational methods for cybersecurity and digital forensics
Numerical methods for privacy-preserving data analysis
Computational methods for explainable AI
Numerical methods for fairness in machine learning
Computational methods for adaptive systems
Numerical methods for cognitive computing
Computational methods for natural user interfaces

In conclusion, Computational Mathematics and its Applications is a promising new journal that seeks to promote the development and advancement of computational mathematics and its applications. With a focus on high-quality peer-reviewed research, the journal aims to provide a platform for researchers, scholars, and practitioners to share their original findings in a wide range of areas, from numerical methods and mathematical modeling to data analysis, artificial intelligence, and more. By promoting interdisciplinary collaborations and facilitating the exchange of ideas and best practices, the journal hopes to contribute to the growth and evolution of the field and its impact on society. With a commitment to open access and adherence to industry regulations, the journal is poised to become an important resource for researchers and practitioners worldwide.