This work programme considers the participation on the following activities: - Analysis of use cases and definition of the specific goals and requisites(e.g., what data should be used) - Collect data and perform pre-processing (e.g., remove noise, damaged data,...) - Describe the data from the power transformers sensors(e.g., through statistical descriptors) - Study the underlying physical models(e.g. electrical model, mechanical model) - Create empirical models using Neural Networks or methods that are more suitable. - Combine physical models with empirical models and yield hybrid models. - Create/adapt the hybrid models for incremental operations and data streams. - Adapt these behavior models to possible data-driven services. This project involves the collaboration of EFACEC, INEGI and MIT Portugal institutions. It is also predicted the collaboration in lectures activities.
Licentiate degree in Computer Science or Electrotechnical, Informatics or Software Engineering or similar
Minimum profile required
- Final graduation mark higher or equal to 13.- Fluency in English (spoken and written)
Good programming and document writing skills Experience in Machine Learning, Data Mining and Power Transformers;
Since 25 Nov 2021 to 10 Dec 2021
Cluster / Centre
Computer Science / Artificial Intelligence and Decision Support