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Visar resultat 1 - 5 av 63 uppsatser som matchar ovanstående sökkriterier.
1. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks
Kandidat-uppsats, Uppsala universitet/Statistiska institutionenSammanfattning : 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. Seasonal Variability of Ice Nucleating Particles (INP) in Southern Sweden
Master-uppsats, Göteborgs universitet / Institutionen för biologi och miljövetenskapSammanfattning : Cloud ice crystals are formed by ice-nucleating particles (INPs). The micro-physical properties of clouds, precipitation formation and the life cycle of clouds are strongly influenced by the presence or absence of ice. Therefore knowledge of atmospheric INP concentrations is crucial to improve weather forecasting and climate projections. LÄS MER
3. Forecasting Monthly Swedish Air Traveler Volumes
Kandidat-uppsats, Uppsala universitet/Statistiska institutionenSammanfattning : In this paper we conduct an out-of-sample forecasting exercise for monthly Swedish air traveler volumes. The models considered are multiplicative seasonal ARIMA, Neural network autoregression, Exponential smoothing, the Prophet model and a Random Walk as a benchmark model. LÄS MER
4. LSTM-based Directional Stock Price Forecasting for Intraday Quantitative Trading
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Deep learning techniques have exhibited remarkable capabilities in capturing nonlinear patterns and dependencies in time series data. Therefore, this study investigates the application of the Long-Short-Term-Memory (LSTM) algorithm for stock price prediction in intraday quantitative trading using Swedish stocks in the OMXS30 index from February 28, 2013, to March 1, 2023. LÄS MER
5. Inflation Index for the House and Content Portfolio : A Model to Calculate the Future Claim Costs for Trygg-Hansa
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : Trygg-Hansa is a Swedish insurance company that specializes in business insurance, home insurance, vehicle insurance, and personal insurance. This work focuses on Trygg-Hansa’s House and Content portfolio, which insures customers’ homes, both the building itself and its contents. LÄS MER