Focus & Scope

The scope of the journal includes, but is not limited to, the following areas:

1. Artificial Intelligence (AI)

  • Knowledge-based systems

  • Reasoning and inference mechanisms

  • Intelligent agents and multi-agent systems

  • AI optimization, heuristics, and metaheuristics

  • Cognitive and adaptive computing

2. Machine Learning (ML)

  • Supervised, unsupervised, and semi-supervised learning

  • Reinforcement learning and deep reinforcement learning

  • Ensemble learning techniques

  • Feature engineering and dimensionality reduction

  • Model evaluation, validation, and performance metrics

3. Deep Learning

  • Neural network architectures

  • Convolutional Neural Networks (CNNs)

  • Recurrent Neural Networks (RNNs), LSTM, GRU

  • Generative models (GANs, VAEs)

  • Transfer learning and pre-trained models

4. Natural Language Processing (NLP)

  • Text mining and sentiment analysis

  • Machine translation

  • Information extraction and information retrieval

  • Speech and language understanding

  • Large language models (LLMs) and chatbot systems

5. Computer Vision

  • Image processing and pattern recognition

  • Object detection, tracking, and classification

  • Video analytics

  • Facial recognition technologies

  • Vision-based autonomous systems

6. Robotics and Intelligent Systems

  • Autonomous and intelligent robots

  • IoT-based intelligent environments

  • Human–robot interaction

  • Motion planning and control algorithms

7. Data Science and Big Data Analytics

  • Predictive modeling

  • Data mining methods

  • Big data processing architectures

  • AI-driven decision support systems

8. Applied AI and Industry Implementations

  • AI applications in healthcare, finance, business, education, agriculture, manufacturing, and smart cities

  • Computational intelligence for solving real-world problems

  • Explainable AI (XAI), AI ethics, transparency, and governance

  • Responsible and sustainable AI practices