MLNLRAFT

Special Issue on Machine Learning with Neutrosophic Logic: Recent Advances and Future Trends

Neutrosophic sets are acquiring significant traction in the solution of numerous real-world decision-making issues involving ambiguity, imprecision, vagueness, incompletion, inconsistency, and indeterminacy. They have been utilized in computational intelligence, decision-making with multiple criteria, image processing, medical diagnoses, etc. This Special Issue solicits original research papers that describe recent developments in neutrosophic sets and logic in soft computing, machine learning, artificial intelligence, big and small data mining, and practical accomplishments.

Topics of interest include but are not limited to

• Applying Neutrosophic Logic and Machine Learning Techniques in Supply Chain Management
• Neutrosophic Multi-criteria Decision Analysis with Machine Learning Techniques
• Big Data with Machine Learning and Neutrosophic Logic
• Reinforcement learning-based architecture for Neutrosophic logic
• Artificial Intelligence with Neutrosophic Logic Systems
• Neutrosophic Logic Systems Architecture
• Neutrosophic Deep Neural Networks
• Machine Learning and Neutrosophic Logic in Electronics
• Supervised Learning of Neutrosophic Logic Systems
• Neutrosophic Systems in Machine Learning and Data Mining
• Explainable Machine Learning and Neutrosophic Logic in Finance
• Machine Learning and Neutrosophic Logic in Real-Life Applications

Important Dates
Submission Portal Open: June 5th, 2023
Submission Deadline: November 1st, 2023
Acceptance Deadline: March 15th, 2024

Lead Guest Editor:

Ibrahim M. Hezam, Statistics and Operations Research Department, College of Sciences, King Saud University, Riyadh, Saudi Arabia.
Email: ialmishnanah@ksu.edu.sa

Guest editors:

Mohamed Abdel-Basset, Head of Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Egypt.
E-mail: mohamedbasset@ieee.org

Karam M. Sallam, School of IT and Systems, University of Canberra, ACT 2601, Australia.
Email: karam.sallam@canberra.edu.au

John Frederick Tapia, Department of Chemical Engineering, De La Salle University, 2401 Taft Avenue, 0922, Manila, Philippines.
Email: john.frederick.tapia@dlsu.edu.ph

Keywords:
Approximate reasoning; Neutrosophic logic; Neural networks; Reinforcement learning; Adaptive control; Machine learning; Deep Learning; Neutrosophic sets.

Manuscript submission information:
The NSWA's submission system (Editorial Manager®) will be open for submissions to our Special Issue from September 5th, 2023. When submitting your manuscript please select the article type SI: MLNLRAFT.