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Showing result 1 - 5 of 1071 essays matching the above criteria.

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

   University essay from Göteborgs universitet/Företagsekonomiska institutionen

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

   Abstract : 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. READ MORE

3. 2. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks

   University essay from Uppsala universitet/Statistiska institutionen

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

   Abstract : 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). READ MORE

4. 3. Data analytics and machine learning for railway track degradation: Using Bothnia Line track measurements for maintenance forecasting

   University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesign

   Author : Elie Roudiere; [2024]
   Keywords : Railway; Track geometry; Machine learning; Statistics; Predictive maintenance; Botniabanan; Järnväg; spårgeometri; maskininlärning; statistik; förebyggande underhåll; Botniabanan;

   Abstract : In this paper, a statistical method is developed to improve predictive maintenance on railway track. The problem tackled is being able to predict when the next maintenance event should take place to guarantee a certain track quality class. READ MORE

5. 4. From Investment to Payoff: Exploring the CostImplications of AI Adoption in InventoryManagement Across the Different Phases

   University essay from Jönköping University/Internationella Handelshögskolan

   Author : bashir Kattan; Lilas Sheekh Kalil; Linda Offor-Ugwuka; [2024]
   Keywords : ;

   Abstract : Background and problem discussion: In recent years, there has been increasing recognition ofArtificial intelligence (AI) and its benefits in various sectors, including inventory management,which is a significant component of company expenses. However, adopting AI in inventorymanagement also comes with challenges and expenses before businesses can fully reap itsbenefits. READ MORE

6. 5. Are Distributional Variables Useful for Forecasting With the Phillips Curve?

   University essay from Handelshögskolan i Stockholm/Institutionen för nationalekonomi

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

   Abstract : 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. READ MORE