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- 2024
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Mark
Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
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- Master (Two yrs)
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Mark
Predicting dust storm susceptibility: exploring control strategies with XGBoost models
(
- Master (Two yrs)
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Mark
Utilizing AI to enhance monitoring of fishing activities via cooperative and non-cooperative methods
(
- Master (Two yrs)
- 2023
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Mark
Multi-scale Bark Beetle Predictions Using Machine Learning
2023) In Master Thesis in Geographical Information Science GISM01 20222(
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)
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Mark
A spatio-temporal graph neural network framework for predicting usage efficiency of e-scooter sharing services
(
- Master (Two yrs)
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Mark
Uncovering the spatial relationships between Covid-19 vaccine coverage and local politics in Sweden
2023) In Master Thesis in Geographical Information Science GISM01 20232(
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)
- 2022
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Mark
Optimizing the locations of bike-sharing stations using GPS-based trip data: A Spatio-temporal demand coverage approach
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- Master (Two yrs)
- 2021
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Mark
GIS-based multi-criteria analysis framework for geofence planning of dockless bike-sharing
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- Master (Two yrs)
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Mark
Applying machine learning approaches to model travel choice between micro-mobility services
(
- Master (Two yrs)