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Visar resultat 1 - 5 av 703 uppsatser som matchar ovanstående sökkriterier.

1. 1. Does industry survey data improve GDP forecasting?

   Kandidat-uppsats, Göteborgs universitet/Företagsekonomiska institutionen

   Författare :Oscar Andersson; Ludvig Fornstedt; [2024-03-06]
   Nyckelord :Bayesian; BVAR; Forecasting; GDP; survey data;

   Sammanfattning : This study assesses the integration of industry survey data into Bayesian Vector Auto Regressive (BVAR) models for GDP forecasting in Sweden. Analyzing a combination of macro economic indicators, CPI and unemployment rates, with survey data from NIER, it explores the effects of different variable combinations on the forecasting ability of different models. LÄS MER

3. 2. 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

4. 3. Are Distributional Variables Useful for Forecasting With the Phillips Curve?

   C-uppsats, Handelshögskolan i Stockholm/Institutionen för nationalekonomi

   Författare :Elsa Rosengren; Pippa Johns; [2024]
   Nyckelord :Distributional Variables; Heterogeneous Agents; Inflation; Phillips Curve; Inequality;

   Sammanfattning : Does information on the distribution of wealth and income help us forecast aggregate macroeconomic variables? In this thesis, we study how adding such distributional variables to a standard forecasting model affects the forecast accuracy, in the context of inflation forecasting. Using the simulated inflation forecasting approach of Atkeson and Ohanian (2001), we perform a horse race between a textbook NAIRU Phillips curve to an extension augmented with variables from the wealth and income distributions. LÄS MER

5. 4. Time Series Forecasting on Database Storage

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Pranav Patel; [2024]
   Nyckelord :Machine Learning; Time Series Forecasting; Prediction; Neural Networks; CNN; RNN; Database Storage;

   Sammanfattning : Time Series Forecasting has become vital in various industries ranging from weather forecasting to business forecasting. There is a need to research database storage solutions for companies in order to optimize resource allocation, enhance decision making process and enable predictive data storage maintenance. LÄS MER

7. 5. Long-term Forecasting Heat Use in Sweden's Residential Sector using Genetic Algorithms and Neural Network

   Master-uppsats, Högskolan i Halmstad/Akademin för företagande, innovation och hållbarhet

   Författare :Alireza Momtaz; Mohammad Befkin; [2024]
   Nyckelord :Genetic Algorithm; Neural Network; Forecasting; Heat Use;

   Sammanfattning : In this study, the parameters of population, gross domestic product (GDP), heat price, U-value, and temperature have been used to predict heat consumption for Sweden till 2050. It should be noted that the heat consumption has been considered for multi-family houses. Most multi-family houses (MFH) get their primary heat from district heating (DH). LÄS MER