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Visar resultat 16 - 20 av 50 uppsatser som matchar ovanstående sökkriterier.
16. Värdet av data : en studie på hur skidanläggningar kan dra nytta av data
Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)Sammanfattning : I takt med digitaliseringen blir datadrivet beslutsfattande det nya normala i många branscher. Konkurrensfördelarna är allmänt kända eftersom det hjälper företag att utvecklas. LÄS MER
17. Risk-aware Autonomous Driving Using POMDPs and Responsibility-Sensitive Safety
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Autonomous vehicles promise to play an important role aiming at increased efficiency and safety in road transportation. Although we have seen several examples of autonomous vehicles out on the road over the past years, how to ensure the safety of autonomous vehicle in the uncertain and dynamic environment is still a challenging problem. LÄS MER
18. Belief-aided Robust Control for Remote Electrical Tilt Optimization
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Remote Electrical Tilt (RET) is a method for configuring antenna downtilt in base stations to optimize mobile network performance. Reinforcement Learning (RL) is an approach to automating the process by letting an agent learn an optimal control strategy and adapt to the dynamic environment. LÄS MER
19. Research on Dynamic Offloading Strategy of Satellite Edge Computing Based on Deep Reinforcement Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Nowadays more and more data is generated at the edge of the network, and people are beginning to consider decentralizing computing tasks to the edge of the network. The network architecture of edge computing is different from the traditional network architecture. LÄS MER
20. AI-Driven Meal Planning in the FoodTech Industry: A Reinforcement Learning Approach
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Traditional meal planning for large kitchens is a laborious and complex affair with multiple external constraints imposed on the meal plan, such as a healthy nutrition profile and a low environmental impact, which should be fulfilled while being under budget. This is a tough task for humans but by modelling the process with a Markov Decision Process and using Reinforcement Learning an agent can be taught to create meal plans from constraints. LÄS MER