| KEYWORD |
Fatigue limit prediction by use of machine learning approaches
keywords FATIGUE RESISTENCE, MACHINE LEARNING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS, THERMOGRAPHY
Reference persons RAFFAELLA SESANA
External reference persons Mohsen Dehghampour
Research Groups THEXOR - DIMEAS
Thesis type MODELING AND DATA ANALYSIS
Description The objective of this thesis is to develop regression and classification technologies in machine learning in order to create an accurate model for estimating the fatigue limit from thermographic data sets used in fatigue analysis.
Required skills The ideal candidate will have a comprehensive understanding of the following areas:
The analysis of fatigue limits
Thermographic analysis
Regression Machine Learning
classification machine learning
Artificial Neural Networks
* The ability to implement digitalization is an advantageous quality.
Deadline 25/11/2025
PROPONI LA TUA CANDIDATURA