Sökning: "Förutsägelser"
Visar resultat 6 - 10 av 72 avhandlingar innehållade ordet Förutsägelser.
6. Time, space and control: deep-learning applications to turbulent flows
Sammanfattning : In the present thesis, the application of deep learning and deep reinforcement learning to turbulent-flow simulations is investigated. Deep-learning models are trained to perform temporal and spatial predictions, while deep reinforcement learning is applied to a flow-control problem, namely the reduction of drag in an open channel flow. LÄS MER
7. Företaget som investeringsobjekt : hur placerare och analytiker arbetar med att ta fram ett investeringsobjekt
Sammanfattning : Säg "företag" och man tänker på någon som tillverkar och säljer varor eller tjänster.Den här boken befattar sig inte med det. Avhandlingen tar istället sikte på företaget som investeringsobjekt. Den undersöker hur investerare och aktieanalytiker tillsammans skapar objektet. LÄS MER
8. Dynamical Analysis of Chemical Activity of Sterically Encumbered Lewis acid/base Pairs
Sammanfattning : This licentiate thesis is about the dynamics analysis of chemical reactions involving a stoichiometric mixture of sterically hindered Lewis base (LB) and Lewis acid (LA) – the so-called frustrated Lewis pairs (FLPs). The tool for dynamical description of chemical reactions is the ab initio molecular dynamics (AIMD) simulations together with the calculation of minimum energy paths (MEPs) on the potential energy surfaces (PESs). LÄS MER
9. Aerodynamic Design and Aeromechanical Analysis of Mixed and Radial Flow Turbines : A study on meanline method, stator tilting endwall design and forced response analysis
Sammanfattning : In this energy transition era, turbocharging is still an important technology for the automotive industry to reduce fuel consumption and lower emissions in its vehicles. This importance can be seen from both conventional fossil-fuel powertrains, and emerging applications, such as increased utilization of biofuels along with hydrogen fuel cells. LÄS MER
10. Structured Representations for Explainable Deep Learning
Sammanfattning : Deep learning has revolutionized scientific research and is being used to take decisions in increasingly complex scenarios. With growing power comes a growing demand for transparency and interpretability. The field of Explainable AI aims to provide explanations for the predictions of AI systems. LÄS MER