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Journal of Computational Mathematics and Data Science - Elsevier | 2024 Cite Score: 5.3 | Q2

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Journal of Computational Mathematics and Data Science - Elsevier | 2024 Cite Score: 5.3 | Q2

  • About this Journal:
  • Journal of Computational Mathematics and Data Science publishes high-quality, peer-reviewed research integrating mathematical modeling, computational techniques, and data-driven methods.Journal of Computational Mathematics and Data Science (JCMDS) is a gold open access journal offering authors the opportunity to publish in all areas of computational mathematics and data science.
  • The journal focuses on the interplay between applied mathematics, computer science, and data science to solve complex real-world problems across science, engineering, and industry.Journal of Computational Mathematics and Data Science publishes high-quality papers (original, reviews, or letters) in all areas of modern computational mathematics. More specifically it publishes papers on the development of numerical methods, their theoretical analysis (convergence, complexity, accuracy, and stability), and their applications in sciences and engineering. The journal publishes also review (survey) papers. For survey papers a prior acceptance from the editor-in-chief is necessary. The emphasis of a review paper must be the presentation of new insights into a topic and not only a presentation of known results.
  • It aims to serve as a platform for the development of novel computational algorithms, data analytics frameworks, and mathematical theories that advance the understanding of large-scale and high-dimensional systems.
  • The journal welcomes interdisciplinary contributions that promote methodological innovation and practical applications of computational mathematics in data-intensive domains.

  • Editor-in-Chief:  Prof. Dr. Theodore Simos, PhD

  • Scope of the Journal:
  • Computational mathematics, numerical analysis, and scientific computing.
  • Mathematical modeling and simulation of complex systems.
  • Data science, machine learning, and artificial intelligence algorithms.
  • Optimization techniques, uncertainty quantification, and inverse problems.
  • High-performance computing, parallel algorithms, and data-driven computation.
  • Applications in engineering, physics, biology, finance, and social sciences.
  • Integration of mathematical theory with data analytics and computational tools.
  • Latest Research Topics for PhD in Machine Learning
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  • Latest Research Topics for PhD in Artificial Intelligence
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  • Print ISSN:  27724158

    Electronic ISSN:  

  • Abstracting and Indexing:  Scopus

  • Imapct Factor :  

  • Subject Area and Category:  Artificial Intelligence, Computer Science Applications, Applied Mathematics, Computational Mathematics

  • Publication Frequency:  

  • H Index:  12

  • Best Quartile:

    Q1:  

    Q2:  Artificial Intelligence

    Q3:  

    Q4:  

  • Cite Score:  5.3

  • SNIP:  1.292

  • Journal Rank(SJR):  0.433