
*Neutrosophic Computing and Machine Learning* (NCML) is an academic journal established for the publication of advanced studies in neutrosophy, neutrosophic sets, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic approaches to machine learning, and their applications across various fields. All submitted works should be professional, written in proper English or Spanish, and include a brief review of a problem along with the obtained results. Submissions are checked for plagiarism and self-plagiarism using automated software.
For detailed submission guidelines, please refer to the [Information for Authors](https://fs.unm.edu/NCML/). Manuscripts should be formatted according to the provided [MS Word Template](https://fs.unm.edu/NCML/). To submit an article, please email the file to the editors. For printed issues, contact the editors directly. This is an open-access, non-commercial academic journal with no publication fees.
The University of New Mexico hosts a website dedicated to neutrosophic theories and applications: [https://fs.unm.edu/neutrosophy.htm](https://fs.unm.edu/neutrosophy.htm).
NCML is sponsored by the University of New Mexico, the Neutrosophic Science International Association (NSIA), and its branch, the Asociación Latinoamericana de Ciencia Neutrosóficas. Their respective websites are:
- [https://fs.unm.edu/NCML/](https://fs.unm.edu/NCML/)
- [https://fs.unm.edu/NCML2/](https://fs.unm.edu/NCML2/)
- [https://fs.unm.edu/NCML/Articulos.htm](https://fs.unm.edu/NCML/Articulos.htm)
*Publication Ethics and Malpractice Statement*
NCML is committed to ensuring publication ethics and the quality of articles. The journal aims to publish only original scientific articles that contribute to the field of neutrosophic theories, their applications, and related topics. All parties involved—authors, editors, and reviewers—are expected to adhere to ethical standards. Our [Publication Ethics and Malpractice Statement](https://fs.unm.edu/NCML/) is based on the [Committee on Publication Ethics (COPE)](https://publicationethics.org/) Best Practice Guidelines for Journal Editors.
*Reviewer Report*
The review process involves selecting at least three reviewers worldwide. Each reviewer provides a report and recommendation: accept, reject, or accept after minor or major corrections. Reviewers are asked to complete the [Reviewer Report](https://fs.unm.edu/NCML/).
*Copyright Transfer Agreement*
Authors are required to sign and return the [Copyright Transfer Agreement](https://fs.unm.edu/NCML/).
*Open Access Statement*
Users are free to read, download, copy, distribute, link to, or print the full texts of the articles in this journal without prior permission from the editors or authors. This aligns with the [Budapest Open Access Initiative](https://www.budapestopenaccessinitiative.org/) definition of open access. All articles, volumes, and other materials on this website are licensed under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/), permitting unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
*Download Journal Issues*
Issues of Neutrosophic Computing and Machine Learning are accessible in PDF format through the following links:
- Archives
Visit our [Open-Source Digital Science Library](http://fs.unm.edu/ScienceLibrary.htm).
Authors of neutrosophic articles are included in the [Encyclopedia of Neutrosophic Researchers](https://fs.unm.edu/NCML/).
*Neutrosophic Science International Association (NSIA)*
NSIA has branches in 40 countries worldwide.
*Mailing Address*
Neutrosophic Computing and Machine Learning
University of New Mexico
Department of Mathematics and Sciences
705 Gurley Ave.
Gallup, NM 87301, U.S.A.
Email: smarand@unm.edu
*Copyright*
© Neutrosophic Computing and Machine Learning. This is an open-access journal distributed under the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), permitting unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
*Archiving and Digital Preservation Policies*
We utilize digital preservation services such as Internet Archive (archive.org), a non-profit digital library dedicated to archiving and preserving digital elements of cultural and historical significance
Current Issue
Vol. 39 (2025): July-September