Vol. 3 No. 02 (2023): IJAIML_VOL.3_NO.2_JULY 2023

Articles

• Exploring Machine Learning Techniques to Maximize Efficiency in Construction Industry Electrical and Electronics Engineering Projects

  Nwosu Obinnaya Chikezie Victor1*

  01-19

  • pdf

  DOI: https://doi.org/10.51483/IJAIML.3.2.2023.1-19

• Predicting Style Factor Returns and Group/Sector Returns Using Long and Short-Term Memory (“LSTM”) Deep Learning Neural Networks

  Sanele Makamo1*

  20-27

  • pdf

  DOI: https://doi.org/10.51483/IJAIML.3.2.2023.20-27

• Optimizing Construction Productivity Through Automation and Artificial Intelligence

  Nwosu Obinnaya Chikezie Victor1*

  28-44

  • pdf

  DOI: https://doi.org/10.51483/IJAIML.3.2.2023.28-44

• Enhancing Image-Based Rendering Through Intelligent Machine Learning: Realism, Immersion, and Future Directions

  Bheema Shanker Neyigapula1*

  45-56

  • pdf

  DOI: https://doi.org/10.51483/IJAIML.3.2.2023.45-56

• Revolutionizing Construction: The Impact of Artificial Intelligence on Productivity

  Nwosu Obinnaya Chikezie Victor1*

  57-73

  • pdf

  DOI: https://doi.org/10.51483/IJAIML.3.2.2023.57-73

• Automated Seismic Interpretation: Machine Learning Technologies are Being Used to Develop Automated Seismic Interpretation to Identify Geological Features, Such as Faults and Stratigraphic Horizons

  Nwosu Obinnaya Chikezie Victor1, Lucky Oghenechodja Daniel2

  74-98

  • pdf

  DOI: https://doi.org/10.51483/IJAIML.3.2.2023.74-98