The Electrical Engineering Department of FAMT conducted a one-day workshop for teaching staff to enhance their skills in Artificial Intelligence (AI) and Machine Learning (ML) using MATLAB tools and apps. The workshop focused on Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning (RL), demonstrating how MATLAB’s built-in apps and toolboxes can simplify AI/ML modeling and simulation for electrical engineering applications.
Topics Covered:
- Introduction to MATLAB AI & ML Tools
Overview of MATLAB AI/ML toolboxes such as Deep Learning Toolbox, Reinforcement Learning Toolbox, and Neural Network Toolbox.
Using MATLAB apps like App Designer, Deep Network Designer, and Reinforcement Learning Designer for simulations. - Artificial Neural Networks (ANN) Using MATLAB
Creating, training, and testing ANN models using Neural Network Toolbox.
Applications in load forecasting, fault detection, and predictive control.
Convolutional Neural Networks (CNN) Using MATLAB Apps
Designing CNN models with Deep Network Designer for pattern recognition and signal classification.
Hands-on exercises demonstrating image and signal processing applications. - Reinforcement Learning (RL) Using MATLAB Toolbox
Designing RL agents for adaptive control of electrical systems.
Using Reinforcement Learning Designer to implement reward-based learning strategies.
Hands-On Demonstration
Faculty practiced model creation, training, and simulation in MATLAB apps.
Examples included ANN for battery SOC prediction, CNN for pattern recognition, and RL for optimal motor control.
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