dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Karssenberg, Derek | |
dc.contributor.author | Fatah, Youssef | |
dc.date.accessioned | 2024-08-30T23:02:58Z | |
dc.date.available | 2024-08-30T23:02:58Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/47530 | |
dc.description.abstract | This thesis investigates the effectiveness of using ONNX-based machine learning models to simulate cellular automata, specifically focusing on Conway’s Game of Life. The primary goal is to evaluate how well an ONNX-based probabilistic model can replace the traditional deterministic simulation approach used in PCraster, and to assess its ability to represent and predict the behavior of cellular automata. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | A backend for excuting machine learning models stored in the Open Neural Network Exchange format. | |
dc.title | A backend for excuting machine learning models stored in the Open Neural Network Exchange format. | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | ONNX, Software, Machine learning, Cellular automata | |
dc.subject.courseuu | Applied Data Science | |
dc.thesis.id | 38104 | |