Sökning: "noggrannhet"

Visar resultat 51 - 55 av 1415 uppsatser innehållade ordet noggrannhet.

  1. 51. Data Driven Modeling for Aerodynamic Coefficients

    Master-uppsats, KTH/Matematisk statistik

    Författare :Erik Jonsäll; Emma Mattsson; [2023]
    Nyckelord :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.;

    Sammanfattning : 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. LÄS MER

  3. 52. Comparative analysis of contact and non-contact method for determining the natural frequencies of a bolted joint

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Malin Dyberg; Elvira Troillet; [2023]
    Nyckelord :;

    Sammanfattning : To ensure high assembly quality of components, a proper clamping force in bolted joints is essential. The existing tightening technology rely on torque and angle; however, this thesis proposes a method for obtaining the clamping force of a bolted joint based on measuring the natural frequencies. LÄS MER

  4. 53. Deep Learning-Driven EEG Classification in Human-Robot Collaboration

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Yuan Wo; [2023]
    Nyckelord :Human-robot collaboration; Electroencephalogram signal; Signal Processing Feature Extraction; Deep Learning method; Dilated Convolutional Neural Network; Människa-robot-samarbete; Elektroencefalogram-signal; Signalförädlingsfunktionsutvinning; Djupinlärningsmetod; Dilaterat konvolutionellt neuronnätverk.;

    Sammanfattning : Human-robot collaboration (HRC) occurs when people and robots work together in a shared environment. Current robots often use rigid programs unsuitable for HRC. Multimodal robot programming offers an easier way to control robots using inputs like voice and gestures. LÄS MER

  5. 54. A Comparison of Convolutional Neural Networks used in Melanoma Detection : With transfer learning on the PAD-UFES-20 and ISIC datasets

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Abdi Gobena; [2023]
    Nyckelord :Machine learning; Neural networks; Skin cancer; PAD-UFES-20; ISIC; Maskininlärning; Neuronnätverk; Hudcancer; PAD-UFES-20; ISIC;

    Sammanfattning : Skin cancer is one of the most common forms of cancer, of which melanoma is the most lethal. Early detection is critical to long term survival rates. The use of machine learning to detect melanoma shows promising results in detecting malignant forms. LÄS MER

  7. 55. Implementing a Network Optimized Federated Learning Method From the Ground up

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Gustav Källander; Henning Norén; [2023]
    Nyckelord :;

    Sammanfattning : This bachelor thesis presents the implementation ofa simple fully connected neural network (FCNN) and federatedneural network with stochastic quantization from scratch andcompares their performance. Federated learning enables multipleparties to contribute to a machine learning model withoutsharing their sensitive data. LÄS MER