Essays about: "THESIS on Alternative Learning System"

Showing result 1 - 5 of 58 essays containing the words THESIS on Alternative Learning System.

  1. 1. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

    University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Author : Ilya Ploshchik; [2023]
    Keywords : Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

    Abstract : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. READ MORE

  2. 2. Over-the-Air Federated Learning with Compressed Sensing

    University essay from Linköpings universitet/Kommunikationssystem

    Author : Adrian Edin; [2023]
    Keywords : machine learning; ML; Federated Learning; FL; Over-the-air; Over-the-air computation; OtA; OtA computation; AirComp; Compressed sensing; CS; Iterative Hard thresholding; IHT;

    Abstract : The rapid progress with machine learning (ML) technology has solved previously unsolved problems, but training these ML models requires ever larger datasets and increasing amounts of computational resources. One potential solution is to enable parallelization of the computations and allow local processing of training data in distributed nodes, such as Federated Learning (FL). READ MORE

  3. 3. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    University essay from KTH/Mekatronik och inbyggda styrsystem

    Author : Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Keywords : Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Abstract : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. READ MORE

  4. 4. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Niklas Barth; [2023]
    Keywords : Unsupervised Learning; Multivariate Time Series; Graph Convolutional Neural Networks; Anomaly Detection; Industrial Control System; EtherCAT; Power Station; Electricity Grid;

    Abstract : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. READ MORE

  5. 5. Data Driven Modeling for Aerodynamic Coefficients

    University essay from KTH/Matematisk statistik

    Author : Erik Jonsäll; Emma Mattsson; [2023]
    Keywords : Master s thesis; System identification; Parameter estimation; Ordinary least squares; Machine learning; Aerodynamic coefficients; F18--HARV; Flight simulations.; Masteruppsats; Systemidentifiering; Parameteruppskattning; Minstakvadratmetoden; Maskininlärning; Aerodynamiska koefficienter; F18-HARV; Flygsimuleringar.;

    Abstract : Accurately modeling aerodynamic forces and moments are crucial for understanding thebehavior of an aircraft when performing various maneuvers at different flight conditions.However, this task is challenging due to complex nonlinear dependencies on manydifferent parameters. READ MORE