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Visar resultat 1 - 5 av 609 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Does industry survey data improve GDP forecasting?

    Kandidat-uppsats, Göteborgs universitet/Företagsekonomiska institutionen

    Författare :Oscar Andersson; Ludvig Fornstedt; [2024-03-06]
    Nyckelord :Bayesian; BVAR; Forecasting; GDP; survey data;

    Sammanfattning : This study assesses the integration of industry survey data into Bayesian Vector Auto Regressive (BVAR) models for GDP forecasting in Sweden. Analyzing a combination of macro economic indicators, CPI and unemployment rates, with survey data from NIER, it explores the effects of different variable combinations on the forecasting ability of different models. LÄS MER

  3. 2. Teacher characteristics and choicesand their effects on reading achievement: A comparision between Sweden and Quebec

    Master-uppsats, Göteborgs universitet/Institutionen för pedagogik och specialpedagogik

    Författare :Andrea Barber; [2024-01-12]
    Nyckelord :PIRLS 2011; reading achievement; SEM; cross-country comparison; teacher and classroom factors;

    Sammanfattning : Purpose. The purpose of this study is to compare teacher and classroom factors that are believed to affect students’ reading achievement scores at the fourth grade level by using PIRLS 2011 dataset. LÄS MER

  4. 3. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Lisa Linard Pedersen; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER

  5. 4. Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Zeyuan Wu; [2024]
    Nyckelord :Machine Learning; Diagnosis of Sepsis; XGBoost; Logistic Regression; Mathematics and Statistics;

    Sammanfattning : Sepsis, a serious medical condition often leading to patients requiring intensive care, has prompted numerous scientists to employ mathematical techniques to aid in its diagnosis. This thesis uses logistic regression and a machine learning technique, XGBoost, to predict true sepsis (as opposed to sepsis mimics) and culture-positive sepsis (among true sepsis) in critical care using blood test results, physiological measurements and other patient characteristics. LÄS MER

  7. 5. Data analytics and machine learning for railway track degradation: Using Bothnia Line track measurements for maintenance forecasting

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Elie Roudiere; [2024]
    Nyckelord :Railway; Track geometry; Machine learning; Statistics; Predictive maintenance; Botniabanan; Järnväg; spårgeometri; maskininlärning; statistik; förebyggande underhåll; Botniabanan;

    Sammanfattning : In this paper, a statistical method is developed to improve predictive maintenance on railway track. The problem tackled is being able to predict when the next maintenance event should take place to guarantee a certain track quality class. LÄS MER