Sökning: "Parameter Optimization"

Visar resultat 1 - 5 av 329 uppsatser innehållade orden Parameter Optimization.

  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. Computational Fluid Dynamics and Modeling of a Free Surface Flow

    Master-uppsats, KTH/Skolan för teknikvetenskap (SCI)

    Författare :Mathieu Marmier; [2023]
    Nyckelord :CFD; Free Surface Flow; VOF; STAR-CCM ; Multiphase Simulation; Nuclear Engineering; Fluid Mechanics;

    Sammanfattning : This project deals with the CFD modelling of a free surface flow. The aim is to develop and validate a fast and accurate numerical model for stratified two-phase flows. Volume of Fluid (VOF) multiphase model is employed. The purpose is to use the developed numerical model for the design of an element within a compact nuclear reactor. LÄS MER

  4. 3. Optimising Machine Learning Models for Imbalanced Swedish Text Financial Datasets: A Study on Receipt Classification : Exploring Balancing Methods, Naive Bayes Algorithms, and Performance Tradeoffs

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Li Ang Hu; Long Ma; [2023]
    Nyckelord :Imbalanced datasets; Swedish text financial datasets; Accuracy; Matthews correlation coefficient; Recall; Multinomial Naive Bayes; SMOTE; TomekLinks; Performance optimization;

    Sammanfattning : This thesis investigates imbalanced Swedish text financial datasets, specifically receipt classification using machine learning models. The study explores the effectiveness of under-sampling and over-sampling methods for Naive Bayes algorithms, collaborating with Fortnox for a controlled experiment. LÄS MER

  5. 4. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

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

    Författare :Jiayi Feng; [2023]
    Nyckelord :DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

    Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER

  7. 5. Robust Portfolio Optimization with Correlation Penalties

    Master-uppsats, KTH/Matematisk statistik

    Författare :Pelle Nydahl; [2023]
    Nyckelord :Portfolio Optimization; Portfolio Allocation; Robust Optimization; Correlation; Risk Factor Model; EMA Filtering; Weighted Linear Regression; Portföljoptimering; Portföljallokering; Robust optimering; Korrelation; Riskfaktor-modell; EMA-filtrering; Viktad linjär regression;

    Sammanfattning : Robust portfolio optimization models attempt to address the standard optimization method's high sensitivity to noise in the parameter estimates, by taking an investor's uncertainty about the estimates into account when finding an optimal portfolio. In this thesis, we study robust variations of an extension of the mean-variance problem, where an additional term penalizing the portfolio's correlation with an exogenous return sequence is included in the objective. LÄS MER