Sökning: "ARIMA modeller"
Visar resultat 1 - 5 av 20 uppsatser innehållade orden ARIMA modeller.
1. Predicting Drought Hazard In Sweden Using Google Earth Engine And Machine Learning Approach
Master-uppsats, KTH/Hållbar utveckling, miljövetenskap och teknikSammanfattning : Drought, being one the most complex natural hazards, has a significant impact on society. To mitigate the impact and risk, it is crucial to be able to forecast drought, which is a challenging task. Nowadays, with technology innovations, large amounts of remote sensing data is available on the cloud. LÄS MER
2. Machine learning embedded automation in financial forecasting : A quantitative case study at Ericsson
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : In today’s increasingly data-driven world, time series forecasting is becoming a prevalent practice. Business executives can make better decisions aided by insights from financial forecasts. LÄS MER
3. Interventionsanalys av Covidpandemins påverkan på antal flygpassagerare : En studie om flygandet i Sverige under år 2020
Kandidat-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : År 2020 drabbades Sverige och världen av en pandemin Covid-19. Pandemin har en stor påverkan på flygbranschen enligt tidigare undersökningar. LÄS MER
4. Forecasting prices of Bitcoin and Google stock with ARIMA vs Facebook Prophet
Kandidat-uppsats, Högskolan Väst/Avd för juridik, ekonomi, statistik och politikSammanfattning : In this thesis we have presented econometrics and forecasts of Bitcoin and Google (GOOG) prices. We have implemented two models, one traditional, “ARIMA” and a relatively new one, “Prophet model” by using Facebook Prophet (ML). Machine learning is still new in the economic field, it has been rewarding to learn its capability. LÄS MER
5. A Comparison of Recurrent Neural Networks Models and Econometric Models for Stock Market Predictions
Master-uppsats, Umeå universitet/Institutionen för fysikSammanfattning : It is well known that the stock market is highly volatile, so stock price prediction is a very challenging task. However, in order to make a profit or to understand the equity market, many investors and researchers use various statistical, econometric, and neural network models to make the best stock price predictions possible. LÄS MER