Sökning: "deterministic methods"
Visar resultat 6 - 10 av 106 uppsatser innehållade orden deterministic methods.
6. Conform with the Wind : Processing short-term ensemble forecasts with conformal based methods for probabilistic wind-speed forecasting
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : Forecasting wind has always been an interesting subject, and as large parts of the world are relying more on wind for power production it is becoming even more important to have reliable forecasts. Probabilistic forecasts, where distributions are predicted in contrast to deterministic forecasts, are impor- tant for informed decision making. LÄS MER
7. Deep learning for temporal super-resolution of 4D Flow MRI
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : The accurate assessment of hemodynamics and its parameters play an important role when diagnosing cardiovascular diseases. In this context, 4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique that facilitates hemodynamic parameter assessment as well as quantitative and qualitative analysis of three-directional flow over time. LÄS MER
8. High tide flooding in near future projections for popular travel destinations
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : High tide flooding (HTF) is becoming more common in coastal regions of the United States, although this phenomenon remains largely undocumented in published literature from other parts of the world. No matter the emissions scenario over the next decades, sea level rise (SLR) is projected to continue worldwide until at least the end of the 21st century, continually pushing the frequency and severity of HTF. LÄS MER
9. Computational modelling of quorum sensing using cascade delay
Kandidat-uppsats,Sammanfattning : The scope of this project was to implement a quorum sensing model capable of synchronised oscillations from the article ”A synchronized quorum of genetic clocks” [1] in the software framework URDME [2]. The model consists of a system of partial differential equations describing time delayed and coupled biochemical reactions. LÄS MER
10. Deep Reinforcement Learning Approach to Portfolio Optimization
Kandidat-uppsats, Lunds universitet/Nationalekonomiska institutionenSammanfattning : This paper evaluates whether a deep reinforcement learning (DRL) approach can be implemented, on the Swedish stock market, to optimize a portfolio. The objective is to create and train two DRL algorithms that can construct portfolios that will be benchmarked against the market portfolio, tracking OMXS30, and the two conventional methods, the naive portfolio, and minimum variance portfolio. LÄS MER