The Journal of Combinatorial Mathematics and Combinatorial Computing (JCMCC) is a peer-reviewed, interdisciplinary journal dedicated to advancing the fields of combinatorial mathematics and computing, computer sciences and AI. The journal provides a platform for researchers, mathematicians, computer scientists, and practitioners to disseminate their original research, cutting-edge developments, and innovative applications in these interconnected disciplines.
The scope of JCMCC includes, but is not limited to, the following topics:
1. Combinatorial Mathematics and Computing:
- Graph theory and applications
- Combinatorial optimization
- Enumerative combinatorics
- Ramsey theory
- Algebraic combinatorics
- Combinatorial designs
- Coding theory
- Extremal combinatorics
- Partitions and compositions
- Combinatorial algorithms and complexity
- Computational combinatorics
- Algorithms for combinatorial problems
- Computational complexity of combinatorial tasks
- Combinatorial aspects of computer science and information technology
- Computational graph theory
- Network analysis and algorithms
- Computational combinatorial optimization
2. Computer Sciences and Artificial Intelligence (AI):
- Machine Learning
- Deep Learning
- Natural Language Processing (NLP)
- Computer Vision
- Expert Systems
- Knowledge Representation and Reasoning
- Reinforcement Learning
- Fuzzy Logic
- Evolutionary Algorithms
- Swarm Intelligence
- Neural Networks
- Robotics and Automation
The journal also focuses on the interdisciplinary applications of the topics mentioned above in various domains including healthcare, finance, education, automation, and more.
