Sökning: "Seasonal models"

Visar resultat 1 - 5 av 139 uppsatser innehållade orden Seasonal models.

  1. 1. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Klara Enerud; [2024]
    Nyckelord :time series forecasting; ARIMA; recurrent neural networks; LSTM; electricity forecasting; EED forecasting;

    Sammanfattning : Due to the growing share of renewable energy in countries' power systems, the need for precise forecasting of electricity consumption will increase. This paper considers two different approaches to time series forecasting, autoregressive moving average (ARMA) models and recurrent neural networks (RNNs). LÄS MER

  2. 2. The Role of Uni- and Multivariate Bias Adjustment Methods for Future Hydrological Projections and Subsequent Decision-Making

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

    Författare :Anna Merle Liebenehm-Axmann; [2024]
    Nyckelord :Bias adjustment methods; future hydrological climate projections; statistical analysis; future streamflow analysis; biasjusteringsmetoder; framtida hydrologiska projektioner; statistisk analys; framtida vattenförings analys;

    Sammanfattning : Climate models are essential for generating future climate projections. However, due to simplifications, the models can produce systematic differences between output and reality, which is referred to as model bias. Bias adjustment methods aim to reduce this error, which is important for making future projections more reliable. LÄS MER

  3. 3. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments

    Master-uppsats, Linköpings universitet/Datorseende

    Författare :Erica Ingerstad; Liv Kåreborn; [2024]
    Nyckelord :NeRF; Neural Radiance Field; Satellite Imagery; Machine Learning; Deep Learning;

    Sammanfattning : This thesis investigates the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, per- forms in predicting seasonal variations across different months. LÄS MER

  4. 4. Spatio-temporal analysis of COVID-19 in Västra Götaland, Sweden

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Natalia Andreeva; [2023-08-23]
    Nyckelord :;

    Sammanfattning : Spatio-temporal analysis of COVID-19 data with the two different statistical approaches is the main objective of this thesis. The first classical approach, the Endemic-Epidemic framework (Held et al., 2005) is a class of multivariate time-series models for the incidence counts, obtained from the surveillance systems. LÄS MER

  5. 5. INVESTIGATING THE COVARIANCE BETWEEN RAINFALL AND MALE ELEPHANT MOVEMENT - To Reduce Human-Elephant Conflict

    Kandidat-uppsats, Göteborgs universitet / Institutionen för biologi och miljövetenskap; Göteborgs universitet / Institutionen för biologi och miljövetenskap

    Författare :Sara Ros; [2023-06-22]
    Nyckelord :Loxodonta africana; Elephants; Botswana; Human-Elephant Conflict; HEC; HumanWildlife Conflict; HWC; Conservation; Musth; Bulls; Rainfall;

    Sammanfattning : Human-wildlife conflict threatens the survival of a range of species, including the savannah elephant (Loxodonta africana). Villages bordering the Makgadikgadi Pans National Park in Botswana are among the most affected by human-elephant conflict, and it is crucial to identify contributing factors to develop mitigation strategies. LÄS MER