Projecte ofert
Títol: Harnessing Data-Driven Mechanisms for Shape Engineering
Per assignar-vos el projecte us heu de dirigir al director/a perquè us l'assigni.
Director/a: RYZHAKOV, PAVEL
Departament: DECA
Títol: Harnessing Data-Driven Mechanisms for Shape Engineering
Data inici oferta: 26-04-2024 Data finalització oferta: 26-12-2024
Estudis d'assignació del projecte:
GR ENG SIS TELECOMUN- GR ENG SIST AEROESP
- GR ENG TELEMÀTICA
| Tipus: Individual | |
| Lloc de realització: |
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| Nom del segon director/a (UPC): Dra. Angela Ares de Parga | |
| Departament 2n director/a: | |
| Paraules clau: | |
| Data science, neural networks, machine learning | |
| Descripció del contingut i pla d'activitats: | |
| In the realm of automated aerodynamics, the shaping of aircraft forms using operational settings is
deemed essential. This proposal aims to emulate aircraft design by focusing on basic geometric configurations. Through predictive modeling, an understanding is sought regarding how shape features are influenced by operational settings. By employing machine learning and data-driven techniques, efforts will be made to study accurate shape prediction models with eventual applications in engineering real-world aircraft scenarios. Objectives and Tasks 1. Familiarize with pertinent literature on Machine Learning Data-Driven Models, including a comparative analysis of predictive models like Radial Basis Function (RBF) and Neural Networks (NN). 2. Understand the fundamentals of data preprocessing, correlation analysis, and clustering methods to effectively analyze and interpret datasets, incorporating an exploration of OpenCV libraries for image recognition. 3. Familiarize with libraries like TensorFlow and PyTorch, and explore alternative options for creating predictive models. 4. Developing an initial framework to precisely predict shape features, tailored specifically for future applications in aircraft engineering. Responsibilities This project will be supervised by Professor Pavel Ryzhakov, who will guide and oversee the progress of the tasks. Note: The proposed plan is subject to adjustments and refinements based on the availability of resources and consultation with the supervisor. The TFG will be supervised by Prof. P. Ryzhakov and Dr. A. Aares de Parga. |
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| Orientació a l'estudiant: | |
| Programming skills, basic knowledge of machine learning | |
| Requereix activitats hardware: No | |
| Requereix activitats software: No | |
| Horari d'atenció a estudiants per a l'assignació de projecte: |
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