Propagation of uncertainty from observing systems and NWP into hydrological models: COST-731 Working Group 2
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Model-based data-interpretation techniques are increasingly used to improve the knowledge of complex system behavior. Physics-based models that are identified using measurement data are generally used for extrapolation to predict system behavior under othe ...
The variability of the (rain)drop size distribution (DSD) in time and space is an intrinsic property of rainfall, of primary importance for various environmental fields such as remote sensing of precipitation for example. DSD observations are usually colle ...
A short technical subsection for Gaussian Process learning and Uncertainty propagation is presented as required in applications like Model Predictive Control, machine learning and optimization. ...
At the Paul Scherrer Institut (PSI), a methodology for nuclear data uncertainty propagation in CASMO-5M (C5M) assembly calculations is under development. This paper presents a preliminary application of this methodology to C5M decay heat calculations. Appl ...
In this work, we investigate various techniques from the fields of shape analysis and image processing in order to construct a semi-automatic transcription tool for ancient manuscripts. First, we design a shape matching procedure using shape contexts, intr ...
Nuclear data uncertainty propagation based on stochastic sampling ( SS) is becoming more attractive while leveraging modern computer power. Two variants of the SS approach are compared in this paper. The Total Monte Carlo (TMC) method by the Nuclear Resear ...
Raman assistance in distributed sensors based on Brillouin Optical Time-Domain Analysis (BOTDA) can significantly extend the measurement distance. In this work we have developed a 2 meter resolution long-range Brillouin distributed sensor that reaches 100 ...
Knowledge of a machine tool axis to axis geometric location errors allows compensation and corrective actions to be taken to enhance its volumetric accuracy. Several procedures exist, involving either lengthy individual test for each geometric error or fas ...
In this work, we consider a general form of noisy compressive sensing (CS) when there is uncertainty in the measurement matrix as well as in the measurements. Matrix uncertainty is motivated by practical cases in which there are imperfections or unknown ca ...
At the Paul Scherrer Institute (PSI), a methodology titled PSI-NUSS is under development for the propagation of nuclear data uncertainties into Criticality Safety Evaluation (CSE) with the Monte Carlo code MCNPX. The primary purpose is to provide a complem ...