Sökning: "multi-step"
Visar resultat 1 - 5 av 48 uppsatser innehållade ordet multi-step.
1. Time Series Forecasting on Database Storage
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)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
2. Dataset characteristics effect on time series forecasting : comparison of statistical and deep learning models
Kandidat-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : Time series are points of data measured throughout time in equally spaced periods. They present characteristics such as level, noise, trend, seasonality, and outliers. Time series forecasting is the attempt to predict single or multiple future values. LÄS MER
3. Air quality prediction in metropolitan areas using deep learning methods
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : The rapid growth of the world's urban population shows that people are increasingly moving to cities. In recent decades, the frequent occurrence of smog caused by increasing industrialization has brought environmental pollution to record highs. LÄS MER
4. Tillståndsprocessen för havsbaserad vindkraft - en flaskhals som hindrar utbyggnaden av förnybaraenergikällor?
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Juridiska institutionenSammanfattning : In light of the energy crisis and the aim to invest in renewable energy, offshore wind power has received an increased attention. The elevated status of investments in offshore wind has pointed out the problems with the legal process, which so far hasn’t - at least not in the case of establishment outside Swedish territory - been applied to aparticularly large extent. LÄS MER
5. Demand Forecasting of Outbound Logistics Using Neural Networks
Master-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)Sammanfattning : Long short-term volume forecasting is essential for companies regarding their logistics service operations. It is crucial for logistic companies to predict the volumes of goods that will be delivered to various centers at any given day, as this will assist in managing the efficiency of their business operations. LÄS MER