Sökning: "Optimeringsmetod"

Visar resultat 1 - 5 av 35 uppsatser innehållade ordet Optimeringsmetod.

  1. 1. Robustness Analysis of Perfusion Parameter Calculations

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

    Författare :Alicia Palmér; [2024]
    Nyckelord :Perfusion; Medical image analysis; Dynamic Contrast Enhanced Magnetic Resonance Imaging; Tofts model; Functional imaging; Optimization; T1 map; Perfusion; Medicinsk bildanalys; Dynamisk kontrastförstärkt magnetisk resonanstomografibildtagning; Tofts-modell; Funktionell bildbehandling; Optimering; T1 karta;

    Sammanfattning : Cancer is one of the most common causes of death worldwide. When given optimal treatment, however, the risk of severe illness may greatly be reduced. Determining optimal treatment in turn requires evaluation of disease progression and response to potential, previous treatment. LÄS MER

  3. 2. Portfolio Strategies Under Different Inflationary Regimes

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Mohit Parkash; Diana Halladgi Naghadeh; [2023]
    Nyckelord :Inflation; Regression Analysis; Portfolio Optimization; Markowitz; Efficient Frontier; Asset Allocation; Portfolio Management; Financial Mathematics; Inflation; Regressionsanalys; Portföljoptimering; Markowitz; Effektiv Front; Tillgångsallokering; Portföljförvaltning; Finansiell Matematik;

    Sammanfattning : In 2023, the topic of ongoing inflation is being discussed almost daily as it has become inevitable. The global economy is facing significant uncertainty and downward pressure as several leading developed nations adopted expansionary fiscal policies and quantitative easing monetary policies during the pandemic. LÄS MER

  4. 3. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Giorgio Sacchi; [2023]
    Nyckelord :Explainable AI; Counterfactual Explanations CFEs ; Bayesian Optimization BO ; Black-Box Models; Model-Agnostic; Machine Learning ML ; Efficient Computation; High-Stake Decisions; Förklarbar AI; Kontrafaktuell Förklaring CFE ; Bayesiansk Optimering BO ; Svarta lådmodeller; Modellagnostisk; Maskininlärning; Beräkningsmässigt Effektiv; Beslut med höga insatser;

    Sammanfattning : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. LÄS MER

  5. 4. Tracking Optimization in Agrivoltaic Systems : A Comparative Study for Apple Orchards

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

    Författare :Maddalena Bruno; [2023]
    Nyckelord :Agrivoltaics; Optimization; Light sharing; Apple Orchards; Lantbruk; Optimering; Ljusdelning; Äppelodlingar;

    Sammanfattning : Agrivoltaic (APV) systems, based on the co-location of solar panels and crops, are an innovative solution to land-use conflicts that often arise between agriculture and energy production. Their optimal functioning starts with efficient management and sharing of light between solar panels and underlying plants. LÄS MER

  7. 5. Auto-Tuning Apache Spark Parameters for Processing Large Datasets

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

    Författare :Shidi Zhou; [2023]
    Nyckelord :Apache Spark; Cloud Environment; Spark Configuration Parameter; Resource Utilization; Ridge Regression; Elastic Net; Random Forest; Deep Neural Network; Bayesian Optimization; Particle Swarm Optimization.; Apache Spark; Molnmiljö; Apache Spark konfigurationsparameter; Resursutnyttjande; Ridge-regression; Elastisk nät; Slumpskog; Djupt neuralt nätverk; Bayesiansk optimering; Partikelsvärmsoptimering.;

    Sammanfattning : Apache Spark is a popular open-source distributed processing framework that enables efficient processing of large amounts of data. Apache Spark has a large number of configuration parameters that are strongly related to performance. Selecting an optimal configuration for Apache Spark application deployed in a cloud environment is a complex task. LÄS MER