Sökning: "Random forest"

Visar resultat 11 - 15 av 772 uppsatser innehållade orden Random forest.

  1. 11. Physical Exercise and Fatigue Detection using Machine Learning

    Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Filip Säterberg; Rasmus Nilsson; [2024]
    Nyckelord :Machine Learning; Fatigue Prediction; Data Collection; Supervised learning; Surface Electromyography; Accelerometers; Maskininlärning; Trötthetsförutsägelse; Datainsamling; Övervakad; Ytlig-elektromyografi Accelerometrar;

    Sammanfattning : Monitoring of physical exercise is an important task to evaluate and adapt exercise to provide better exercise results. The Inno-X™ device, developed by Innowearable, is a device that can be used for such monitoring. It collects data using an accelerometer and sEMG sensor. LÄS MER

  3. 12. CNN-LSTM architecture for predicting hazardous driving situations

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Noomi Lindblad; Stefani Platakidou; [2023-10-05]
    Nyckelord :Data science; Machine learning; LSTM; CNN; Vehicle data; Hazardous driving situation; Deep learning;

    Sammanfattning : This study aims to investigate how a CNN-LSTM model can be used together with recorded vehicle data from trucks and external weather data in order to predict a hazardous driving situation. The dataset consists of three-second-long driving snippets from customer and development trucks registered within Europe. LÄS MER

  4. 13. The Power of Credit Scoring: Evaluating Machine Learning and Traditional Models in Swedish Retail Banking

    Master-uppsats, Göteborgs universitet/Graduate School

    Författare :Emma von der Burg; Saga Strömberg; [2023-06-29]
    Nyckelord :;

    Sammanfattning : In this paper, we investigate and compare different credit scoring models, with special attention paid to machine learning approaches outperforming traditional models. We explore a recently proposed method called the PLTR model, which is a combination of machine learning and traditional logistic regression. LÄS MER

  5. 14. DISTRIBUTED ARTIFICIAL INTELLIGENCE FOR ANOMALY DETECTION IN A MODULAR MANUFACTURING ENVIRONMENT

    Magister-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Hana Hodzic; [2023]
    Nyckelord :;

    Sammanfattning : This thesis investigates anomaly detection and classification in a simulated modular manufacturingenvironment using Machine Learning algorithm Random Forest. This algorithm is tested on a localcomputer and an embedded device, specifically the Raspberry PI. LÄS MER

  7. 15. Modeling PFAS Transport in Groundwater - Exploring current approaches and evaluating parameter importance

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Väg- och vattenbyggnad (CI); Lunds universitet/Teknisk geologi

    Författare :Clara Eklund; [2023]
    Nyckelord :PFAS; Groundwater modeling; FEFLOW; Python; Machine learning; Technology and Engineering;

    Sammanfattning : PFAS contamination in drinking water is a current problem, and new regulations for drinking water limits were recently implemented in each member country of the EU in January this year. Understanding the spread of PFAS in groundwater is therefore important to prevent it from reaching drinking water sources. LÄS MER