Sökning: "prediction models"
Visar resultat 21 - 25 av 1094 avhandlingar innehållade orden prediction models.
21. Diabetes Mellitus Glucose Prediction by Linear and Bayesian Ensemble Modeling
Sammanfattning : Diabetes Mellitus is a chronic disease of impaired blood glucose control due to degraded or absent bodily-specific insulin production, or utilization. To the affected, this in many cases implies relying on insulin injections and blood glucose measurements, in order to keep the blood glucose level within acceptable limits. LÄS MER
22. Linear Models of Nonlinear Systems
Sammanfattning : Linear time-invariant approximations of nonlinear systems are used in many applications and can be obtained in several ways. For example, using system identification and the prediction-error method, it is always possible to estimate a linear model without considering the fact that the input and output measurements in many cases come from a nonlinear system. LÄS MER
23. 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
24. Color Prediction and Separation Models in Printing : Minimizing the Colorimetric and Spectral Differences employing Multiple Characterization Curves
Sammanfattning : Color prediction models and color separation models are essential for print device characterization and calibration, from which the profiles used in color management systems are built up. Dot gain refers to the phenomenon in printing causing the printed ink dots appear bigger than their reference size in the original bitmap. LÄS MER
25. Statistical modeling and design in forestry : The case of single tree models
Sammanfattning : Forest quantification methods have evolved from a simple graphical approach to complex regression models with stochastic structural components. Currently, mixed effects models methodology is receiving attention in the forestry literature. LÄS MER