Sökning: "sales"
Visar resultat 21 - 25 av 3111 uppsatser innehållade ordet sales.
21. Forecasting With Feature-Based Time Series Clustering
Master-uppsats, Jönköping University/Tekniska HögskolanSammanfattning : Time series prediction plays a pivotal role in various areas, including for example finance, weather forecasting, and traffic analysis. In this study, time series of historical sales data from a packaging manufacturer is used to investigate the effects that clustering such data has on forecasting performance. LÄS MER
22. Performance evaluation of domestic solar power installations in Sweden
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : In the past two decades the global electricity demand all over the world has increased by 82%, thisis a result of improved living standards, growing populations, electrification of vehicles and growing demand for digital devices. In Sweden, electricity generation from solar power is relatively small and equates to about 0. LÄS MER
23. Uncorking Profits: Fine Wine for the Bottom Line
C-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomiSammanfattning : Using a larger dataset covering a time period not previously studied, we examine the price drivers and investment performance of wines from the five Bordeaux Premier Cru producers during 2013-2023. Our results indicate that prices are significantly impacted by producer, weather quality, yield and age. LÄS MER
24. Sales forecasting for supply chain using Artificial Intelligence
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Supply chain management and logistics are two sectors currently experiencing a transformation thanks to the advent of AI(Artificial Intelligence) technologies. Leveraging predictive analytics powered by AI presents businesses with novel opportunities to streamline their operations effectively. LÄS MER
25. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskapSammanfattning : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. LÄS MER