AI-based Projects
On this page, a selection of projects is displayed, with only those that are accessible to the general public. Projects that involve the private
data of the organisations or individuals are not shown. For collaborations and any enquiries, feel free to send a direct message.
Dynamic Electric Vehicle Charging Pricing for Load Balancing in Power Distribution Networks based on Collaborative DDPG Agents
Key components of the project:
- Solves the load peak-shaving, valley-filling, and load balancing across distribution networks problem in the presence of EVs
- Explores deep reinforcement learning problem for collaborative control and optimisation
- Compares the performance of the following agents: DDPG, SAC and PPO
- Show the forecasting of the real-world load data using ML algorithms: polynomial regression, XGBoost, and neural networks
The technical write-up can be found at:
document
Github link to code can be found at:
repository
Multi-level Dynamic Pricing for Electric Vehicles Charging to Balance Load in Distribution Networks Using Q-Learning
Key components of the project:
- Also solves the load peak-shaving, valley-filling, and load balancing across distribution networks problem in the presence of EVs
- Explores advanced data manipulation and engineering to prepare for applied reinforcement learning
- Uses Q-learning agents and custom logic compute for optimisation and control
Github link to code can be found at:
repository
Electricity Theft Detection in Smart Grids Based on Deep Neural Network
Key components of the project:
- Solves electricity theft problem based electricity consumption data of the customers
- Uses novel feature engineering techniques to determine which users steal electricity and which ones do not
- Uses the deep neural network for high-accuracy classification results
The technical write-up can be found at:
document
Building a regression model to predict concrete compressive strength using the deep learning Keras library
Key components of the project:
- Utilises Keras library for concrete strength prediction based on the dataset of the quantities of the ingredients required
- Explores advanced data manipulation to prepare for applied regression algorithm
- Uses neural network-based regression
Github link to code can be found at:
repository
Waste Products Images Classification Using Transfer Learning
Key components of the project:
- Applies transfer learning using the VGG16 model for image classification
- Prepares and preprocesses image data for a machine learning task
- Fine-tunes a pre-trained model to improve classification accuracy
- Visualizes model predictions on test data
Github link to code can be found at:
repository
Satellite Images Classification
Key components of the project:
- Applies transfer learning using the VGG16 model for image classification
- Prepares and preprocesses image data for a machine learning task
- Fine-tunes a pre-trained model to improve classification accuracy
- Visualizes model predictions on test data
Github link to code can be found at:
repository