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Visar resultat 1 - 5 av 47 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Prevalent Discord. Exploring and estimating the prevalence of the type of user disagreement on news media Facebook posts discussing the Colombian peace process (2020-2022)

    Master-uppsats, Lunds universitet/Graduate School

    Författare :Luis Felipe Villota Macias; [2024]
    Nyckelord :Agonistic peace; antagonism; big data analytics; binary logistic regression; computational content analysis; Colombia; Colombian peace process; discord; Facebook; machine learning; peace process; public opinion and sentiment; social media; Law and Political Science; Social Sciences;

    Sammanfattning : This thesis is dedicated to exploring and understanding public reactions within negotiated peace settlements based on social media data. Concretely, to modeling public opinion and sentiment within the context of the Colombian peace process using a curated dataset of N= ~1. LÄS MER

  3. 2. 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

  4. 3. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

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

    Författare :Ilya Ploshchik; [2023]
    Nyckelord :Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

    Sammanfattning : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. LÄS MER

  5. 4. Sales forecasting for supply chain using Artificial Intelligence

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

    Författare :Vaibhav Mittal; [2023]
    Nyckelord :AI; sales forecasting; supply chain; predictive analytics; AI; försäljningsprognoser; supply chain; predictiv analys;

    Sammanfattning : Supply chain management and logistics are two sectors currently experiencing a transformation thanks to the advent of AI(Artificial Intelligence) technologies. Leveraging predictive analytics powered by AI presents businesses with novel opportunities to streamline their operations effectively. LÄS MER

  7. 5. Low-No code Platforms for Predictive Analytics

    Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Soma Karmakar; [2023]
    Nyckelord :Low code; no code; Predictive analytics; databricks; azure; AWS; Google cloud;

    Sammanfattning : In the data-driven landscape of modern business, predictive analytics plays a pivotal role inanticipating and mitigating customer churn—a critical challenge for organizations. However, thetraditional complexities of machine learning hinder accessibility for decision-makers. LÄS MER