In this work we present a study about cognitive agents that have to learn how their different information sources can be more or less trustworthy in different situations and with respect to different hydrogeological phenomena. We introduced an ad-hoc Bayesian trust model that we created and used in the simulations. We also describe the realized platform that can be manipulated in order to shape...

This paper presents an analysis of how day-ahead electricity spot prices are affected by day-ahead wind power forecasts. Demonstration of this relationship is given as a test case for the Western Danish price area of the Nord Pool’s Elspot market. Impact on the average price behaviour is investigated as well as that on the distributional properties of the price. By using a non-parametric regres...

An operational hydrological ensemble forecasting system based on a meteorological ensemble prediction system (M-EPS) coupled with a hydrological model searches to capture the uncertainties associated with the meteorological prediction to better predict river flows. However, the structure of the hydrological model is also an important source of uncertainty that has to be taken into account. This...

We present a framework for predicting the conditional distributions of future observations that is well suited for skewed, fat-tailed, and multi-modal time series. This framework allows to address questions about the nature of an observed time series, such as: Are there discrete subprocesses underlying the observed data? If so, do they exhibit a hidden Markov structure, or are they better descr...

Data envelopment analysis (DEA) has been used as a tool for evaluating past accomplishments in the banking industry. However, due to a time lag, the results usually arrive too late for the evaluated banking institutions to react timely. This paper makes advanced predictions of the performances of 24 commercial banks in Taiwan based on their financial forecasts. The forecasts based on uncertain ...

An observing system simulation experiment (OSSE) has been carried out to evaluate the 1 impact of a hybrid ensemble-variational data assimilation algorithm for use with the National 2 Centers for Environmental Prediction (NCEP) global data assimilation system. An OSSE 3 provides a controlled framework for evaluating analysis and forecast errors since a truth is 4 known. In this case, the nature...