The Sustainable Machine Intelligence Journal (SMIJ) is a premier scientific publication dedicated to the exploration and advancement of sustainable approaches in the field of machine intelligence. SMIJ provides a platform for researchers, engineers, and practitioners to share innovative research findings, methodologies, and applications that integrate machine intelligence with sustainable practices. By bridging the gap between machine intelligence and sustainability, SMIJ aims to foster a deeper understanding of how intelligent technologies can contribute to environmental, social, and economic sustainability. The journal showcases cutting-edge research and promotes interdisciplinary collaboration, making it an indispensable resource for academics, industry professionals, and policymakers striving for a more sustainable future through the power of intelligent systems.
Publishing Mode and Access Fees
There are no article processing or publishing charges.
Sustainable Machine Intelligence Journal (SMIJ) is a Gold Open Access journal; online readers don't have to pay any fees.
Editor(s)-in-Chief
Mohamed Abouhawwash (ORCID, Scopus)
Affiliation: Department of Computational Mathematics
Science and Engineering, College of Engineering, Michigan State University, East Lansing, MI, USA.
Research Interest: Machine Learning, Image Processing, Statistics and Mathematics.
Email: abouhaww@msu.edu
Anand Nayyar
Researcher profiles: (ORCID , Scholar , Scopus)
Affiliation: School of Computer Science, Faculty of Information Technology, Duy Tan University, Da Nang, Viet Nam
E-mail: anandnayyar@duytan.edu.vn
Co-Editors-in-Chief
Victor Chang
Researcher profiles: | Website | Scopus| Scholar| ORCID|
Affiliation: Aston Business School, Aston University, United Kingdom.
Email: v.chang1@aston.ac.uk
Full Editorial Team
Current Issue
Vol. 7 (2024): Sustainable Machine Intelligence
Published: 01-04-2024
Research Article
Sustainable Machine Intelligence Journal (SMIJ) publishes high-quality scientific papers that significantly contribute to the field of machine intelligence and its applications real-world scenarios. The material published is of high quality and relevance, written in a manner that makes it accessible to all of this wide-ranging readership. Preference will be given to papers studying machine intelligence solutions and implications on sustainability within computer science.
Aims and Scope: The principal aim of the journal is to bring together the latest research and development in various fields of sustainable machine intelligence. We would like to highlight those papers should refer to Aims and scope, but they are not limited to.
Publication Frequency: This journal is published quarterly.
Open Access
This is an open-access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author.
The acceptance rate of SMIJ is 16% of the more than 143 major manuscripts it receives annually. In 2023, the median time for an initial editorial decision for submitted manuscripts was 5 days; the median time from submission to acceptance for all articles was 15 weeks and 9 days from acceptance to online publication.
Articles from the Sustainable Machine Intelligence Journal (SMIJ) have been accepted and posted by the scientific archives (arXiv) of Cornell University, New York City.
Publisher:
- Publisher's Name: Sciences Force
- Publisher's Address: Five Greentree Centre, 525 Route 73 North, STE 104 Marlton, New Jersey 08053.
- Tel: +1 (509) 768-2249
- Email: smij@sciencesforce.com