Journal of Algorithms and Computational Technology

Aims & Scope

Journal of Algorithms & Computational Technology is a peer-reviewed open access journal serving an interdisciplinary community of researchers from both academia and industry.

Original research papers describing mathematical methods, numerical methods, and computational technology in the development of engineering solutions and/or computational analysis addressing a broad range of industrial problems arising from, but not limited to, bio-medical science, economics, engineering, finance, life science, medical biology, and science, are welcome.

The journal is fundamentally different from many journals of numerical analysis, computational analysis, and algorithms.

The acceptance of papers is judged on the use of mathematical techniques and/or engineering methodology in the computational analysis and simulations of complex industrial and real life problems in the above areas.

Articles describing carefully tested computational techniques, including post-processing visualisation, for real life problems are welcome on the basis of the above criteria.

Articles involving numerical or mathematical analysis must be driven by applications with industrial and real life problems or their simplified versions.

Longer papers surveying recent progress in the field of computational technology and algorithms are also welcome.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Mathematics, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 2,000.00 USD. Learn more.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Prediction of benign and malignant breast cancer using data mining techniques

  Citation: 221

  Authors: Vikas, Saurabh, BB

• Parallel Support Vector Machines Applied to the Prediction of Multiple Buildings Energy Consumption

  Citation: 102

  Authors: Hai Xiang, Frédéric

• Feature Selection for Predicting Building Energy Consumption Based on Statistical Learning Method

  Citation: 81

  Authors: Hai-Xiang, Frédéric

• Sigmis: A Feature Selection Algorithm Using Correlation Based Method

  Citation: 76

  Authors: E. Chandra, E.

• Forest fire image recognition based on convolutional neural network

  Citation: 69

  Authors: Yuanbin, Langfei, Jieying

• Finite Difference Approximation for Two-Dimensional Time Fractional Diffusion Equation

  Citation: 57

  Authors: P., F.

• The Acoustic Resonance of Rectangular and Cylindrical Cavities

  Citation: 47

  Authors: A

• Fractional Differential Analysis for Texture of Digital Image

  Citation: 47

  Authors: PU

• Efficient Parameter Estimation and Implementation of a Contour Integral-Based Eigensolver

  Citation: 46

  Authors: Tetsuya, Yasunori, Hiroto

• Outlier detection algorithm based on k-nearest neighbors-local outlier factor

  Citation: 41

  Authors: He, Lin, Peng, Feng