Sökning: "Weather Classification"

Visar resultat 1 - 5 av 48 uppsatser innehållade orden Weather Classification.

  1. 1. Exploring patterns in risk factors for bark beetle attack during outbreaks triggered by drought stress with harvester data on attacked trees: A case study in Southeastern Sweden

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Nikolaos Kouskoulis; [2023]
    Nyckelord :Geography; GIS; Geographic Information Science; Forest ecosystems; Bark beetle outbreak; Southeastern Sweden; Predisposing factors; Triggering factors; Drought stress; Earth and Environmental Sciences;

    Sammanfattning : ABSTRACT Raising temperatures and climate variability have intensified extreme weather events worldwide. These extremes can enhance and trigger possible pest outbreaks. Bark beetle attacks have become a major concern in regions with extensive spruce forest areas. Southeastern Sweden has faced repeated outbreaks resulting in widespread tree loss. LÄS MER

  3. 2. Improvement of Wind Power Forecasting and Prediction of Production Losses Caused by Ice Formation on Wind Turbine Blades : - A Machine Learning Approach

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Emelie Sjökvist; [2023]
    Nyckelord :;

    Sammanfattning : In the ongoing climate crisis, transitioning to renewable energy sources is essential to manage the increasing energy demand. One such renewable energy source is the weather-dependent energy source, wind power. Many wind farms are located in Cold Climate (CC) regions, known for their vast potential for wind power production. LÄS MER

  4. 3. Improving Visibility Forecasts in Denmark Using Machine Learning Post-processing

    Master-uppsats, Uppsala universitet/Luft-, vatten- och landskapslära

    Författare :August Thomasson; [2023]
    Nyckelord :visibility forecast; fog; machine learning; numerical weather predicition; XGBoost; Random Forest; siktprognos; dimma; maskininlärning; numerisk vädermodell; XGBoost; Random Forest;

    Sammanfattning : Accurate fog prediction is an important task facing forecast centers since low visibility can affect anthropogenic systems, such as aviation. Therefore, this study investigates the use of Machine Learning classification algorithms for post-processing the output of the Danish Meteorological Institute’s operational Numerical Weather Prediction (NWP) model to improve visibility prediction. LÄS MER

  5. 4. Planteringspunktens påverkan på plantöverlevnad

    Kandidat-uppsats, SLU/School for Forest Management

    Författare :Albin Lindberg; Oskar Lindström; [2023]
    Nyckelord :planteringspunkt; plantöverlevnad; vitalitet;

    Sammanfattning : Skogsvårdslagen har sedan 1903 satt krav på återväxt på avverkade skogsmarker. Skyddet för dessa plantor har historiskt gått från kemisk plantbehandling till mekaniskt skydd och olika former av markbehandling. LÄS MER

  7. 5. Fog detection using an artificial neural network

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Quanwei Li; Tiancheng Ma; [2023]
    Nyckelord :Machine Learning; Deep Learning; Image Analysis; Computer Vision; Mathematics and Statistics;

    Sammanfattning : This project studies a method of image-based fog detection directly from a camera without using the transmissometer. Fog can be detected using transmissometers which could be a very costly approach. This thesis presents an image-based approach for fog detection using Artificial Neural networks. LÄS MER