International Conference on Artificial Intelligence and Application 2024

AIA 2024 will be the most comprehensive conference focused on the various aspects of advances in Artificial Intelligence and Application. Our Conference provides a chance for academic and industry professionals to discuss recent progress in the area of Artificial Intelligence and Application.

The goal of this conference is to bring together researchers from academia and industry as well as practitioners to share ideas, problems, and solutions relating to the multifaceted aspects of Artificial Intelligence and Application.

All papers accepted and registered will be included in STEM Proceedings and selected papers will be included in SCOPUS and EI journals

Tracks of the Conferences

AI and Evolutionary Algorithms
Algebraic Biology
Ant colony optimization
Applications in Bioinformatics
Approximate Reasoning
Architectures of Intelligent Systems
Aspects of knowledge structures
Aspects of natural language processing
Aspects of text technology
Automated problem solving
Bayesian methods
Bioinformatics and computational biology
Biological network analysis
Biostatistics
Brain models / cognitive science
Combining multiple knowledge sources in an integrated intelligent system
Computational Science
Constraint-based reasoning and constraint programming
Cross-Entropy method
Data Mining
Decision support systems
Constructions technology economy and management
Contracting and Legal Issues
Data Sensing and Analysis
Decision Support Systems
Distributed AI algorithms and Techniques
Emerging Technologies
Evaluation of AI tools
Evolutionary Computation
Expert systems
Fuzzy logic, modeling, control and soft computing
Gaussian graphical models
General issues in graph and tree mining
Grammatical inference
Granular Computing
Graph learning based on graph grammars
Heuristic optimization techniques
Hierarchical learning models
High-throughput data analysis
Hybrid Intelligent Systems
Image processing and understanding (interpretation)
Inductive learning and applications
Information-theoretical approaches to graphs
Integration of AI with other technologies
Intelligent agents
Intelligent databases
Intelligent information fusion
Knowledge acquisition and discovery techniques
Knowledge networks and management
Knowledge-intensive problem solving techniques
Languages and programming techniques for AI
Learning and adaptive sensor fusion
Machine learning
Markov chain Monte Carlo (MCMC) methods
Meta learning
Motif search
Multi-criteria reinforcement learning
Multiple hypothesis testing
Multisensor data fusion using neural and fuzzy techniques
Natural language processing
Nature Inspired Methods
Neural networks and applications
Real-world applications of Intelligent Systems
Particle filter
Reasoning strategies
Reinforcement learning
Robotics
Search and meta-heuristics
Simulated annealing
Social intelligence (markets and computational societies)
Statistical learning theory
Stochastic optimization
Supervised and unsupervised classification of web data
Time series prediction
Topics on satisfiability
Unsupervised and Supervised Learning
Web Mining