Avancerad sökning
Visar resultat 1 - 5 av 160 avhandlingar som matchar ovanstående sökkriterier.
1. Reliable Uncertainty Quantification in Statistical Learning
Sammanfattning : Mathematical models are powerful yet simplified abstractions used to study, explain, and predict the behavior of systems of interest. This thesis is concerned with their latter application as predictive models. LÄS MER
2. Prediction and postdiction under uncertainty
Sammanfattning : An intelligent agency requires the capability to predict what the world looks like as a consequence of its actions. It also needs to explain present observations in order to infer previous states. This thesis proposes an approach to realize both capabilities, that is prediction and postdiction based on temporal information. LÄS MER
3. From data to decision - learning by probabilistic risk analysis of biological invasions
Sammanfattning : Predicting an uncertain future with uncertain knowledge is a challenge. The success of efforts to preserve biodiversity, to maintain biosecurity and to reduce a negative impact from climate change, depend on scientifically based predictions of future events. LÄS MER
4. Observational Uncertainties in Water-Resources Modelling in Central America : Methods for Uncertainty Estimation and Model Evaluation
Sammanfattning : Knowledge about spatial and temporal variability of hydrological processes is central for sustainable water-resources management, and such knowledge is created from observational data. Hydrologic models are necessary for prediction for time periods and areas lacking data, but are affected by observational uncertainties. LÄS MER
5. Spatial sampling and prediction
Sammanfattning : This thesis discusses two aspects of spatial statistics: sampling and prediction. In spatial statistics, we observe some phenomena in space. Space is typically of two or three dimensions, but can be of higher dimension. LÄS MER