Sökning: "Reinforcement Learning"

Visar resultat 21 - 25 av 175 avhandlingar innehållade orden Reinforcement Learning.

1. 21. On Deep Machine Learning Based Techniques for Electric Power Systems

   Författare :Ebrahim Balouji; Chalmers tekniska högskola; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Cable faults; phase locked loop; Flicker; Harmonics and Interharmonics; Reinforcement learning; Voltage Dip; Active Power filter; Machine Learning; Voltage fluctuation; Partial Discharges;

   Sammanfattning : This thesis provides deep machine learning-based solutions to real-time mitigation of power quality disturbances such as flicker, voltage dips, frequency deviations, harmonics, and interharmonics using active power filters (APF). In an APF the processing delays reduce the performance when the disturbance to be mitigated is tima varying. LÄS MER

3. 22. Spike-Based Bayesian-Hebbian Learning in Cortical and Subcortical Microcircuits

   Författare :Philip Tully; Anders Lansner; Matthias Hennig; Gordon Pipa; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Bayes rule; synaptic plasticity and memory modeling; intrinsic excitability; naïve Bayes classifier; spiking neural networks; Hebbian learning; neuromorphic engineering; reinforcement learning; temporal sequence learning; attractor network; Computer Science; Datalogi;

   Sammanfattning : Cortical and subcortical microcircuits are continuously modified throughout life. Despite ongoing changes these networks stubbornly maintain their functions, which persist although destabilizing synaptic and nonsynaptic mechanisms should ostensibly propel them towards runaway excitation or quiescence. LÄS MER

4. 23. Data-Efficient Learning of Semantic Segmentation

   Författare :David Nilsson; Mathematical Imaging Group; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; semantic segmentation; embodied learning; active learning; semantic video segmentation; computer vision; deep learning;

   Sammanfattning : Semantic segmentation is a fundamental problem in visual perception with a wide range of applications ranging from robotics to autonomous vehicles, and recent approaches based on deep learning have achieved excellent performance. However, to train such systems there is in general a need for very large datasets of annotated images. LÄS MER

5. 24. Enabling Enterprise Live Video Streaming with Reinforcement Learning and Graph Neural Networks

   Författare :Stefanos Antaris; Sarunas Girdzijauskas; Dimitrios Katsaros; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Graph Neural Networks; Reinforcement Learning; Meta-Learning; Knowledge Distillation; Enterprise Liveo Video Streaming;

   Sammanfattning : Over the last decade, video has vastly become the most popular way the world consumes content. Due to the increased popularity, video has been a strategic tool for enterprises. LÄS MER

7. 25. Learning to Control the Cloud

   Författare :Albin Heimerson; Institutionen för reglerteknik; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Cloud Computing; Reinforcement Learning; Learning-Based Control; Microservices; Datacenter; Autoscaling; Load Balancing; Neural Networks;

   Sammanfattning : With the growth of the cloud industry in recent years, the energy consumption of the underlying infrastructure is a major concern.The need for energy efficient resource management and control in the cloud becomes increasingly important as one part of the solution, where the other is to reduce the energy consumption of the hardware itself. LÄS MER