Sökning: "prediction uncertainty"

Visar resultat 16 - 20 av 160 avhandlingar innehållade orden prediction uncertainty.

  1. 16. Assessment of Experimental, Computational, and Combined EFD/CFD Methods for Ship Performance Prediction

    Författare :Kadir Burak Korkmaz; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; numerical friction line; form factor; CFD; measurement uncertainty; power prediction; EFD; verification and validation; Combined CFD EFD Methods;

    Sammanfattning : In today’s highly competitive market, alongside increasingly stringent regulatory requirements, the precise prediction of ship performance has assumed paramount importance for both design verification and operational evaluations. This thesis addresses the need for a comprehensive assessment of Experimental Fluid Dynamics (EFD), Computational Fluid Dynamics (CFD), and their combination to enhance the accuracy of performance predictions. LÄS MER

  3. 17. Handling severe uncertainty in strategic project appraisal : Methods and applications of context analysis

    Författare :Anton Talantsev; Aron Larsson; David Sundgren; John Ward; Stockholms universitet; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Decision Intelligence; Deep Uncertainty; Scenario Analysis; Multiple Criteria Decision Analysis; Simulation; Context Analysis; Project Appraisal; Risk Assessment; Threat and Opportunity; Computer and Systems Sciences; data- och systemvetenskap;

    Sammanfattning : The long-term success or failure of a strategic project is largely shaped by its context. Therefore, the assessment of the external factors influencing the fulfilment of project long-term goals is vital for the effective project appraisal and planning. LÄS MER

  4. 18. Channel Gain Prediction for Cooperative Multi-Agent Systems

    Författare :Markus Fröhle; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Gaussian processes; channel prediction; multi-agent systems; spatial correlation; wireless ad-hoc networks; parameter learning; distributed algorithms;

    Sammanfattning : In a cooperative multi-agent system (MAS), agents communicate with each other using the wireless medium. As agents move in the environment in order to fulfill the MAS' higher level task, their location changes and so does the wireless communication channel they experience. LÄS MER

  5. 19. Fatigue Life Prediction in Service - A Statistical Approach

    Författare :Thomas Svensson; Göteborgs universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; fatigue life; sequential effects; variable amplitude fatigue; prediction uncertainties; variable amplitude fatigue;

    Sammanfattning : This thesis treats the problem of fatigue life prediction. The emphasis is on the development of simplified methods, intended to be used in engineering design and the starting point is the established methods for fatigue prediction in service, namely the Wöhler curve, the Paris´ law and the Palmgren-Miner law of cumulative damage. LÄS MER

  7. 20. Trustworthy explanations : Improved decision support through well-calibrated uncertainty quantification

    Författare :Helena Löfström; Ulf Seigerroth; Ulf Johansson; Patrick Mikalef; Jönköping University; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Explainable Artificial Intelligence; Interpretable Machine Learning; Decision Support Systems; Uncertainty Estimation; Explanation Methods;

    Sammanfattning : The use of Artificial Intelligence (AI) has transformed fields like disease diagnosis and defence. Utilising sophisticated Machine Learning (ML) models, AI predicts future events based on historical data, introducing complexity that challenges understanding and decision-making. LÄS MER