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We present a new type of the EnKF for data assimilation in spatial models that uses diagonal approximation of the state covariance in the wavelet space to achieve adaptive localization. The efficiency of the new method is demonstrated on an example.
The purpose of our work is to develop a methodology for quantifying and analyzing social processes. We propose a mechanism for measuring political activity and arguing the choice of analysis methods. Our practical studies have shown a correlation between various types of political activities. Proposed technique will allow us to simulate different political situations in the state and predict possible...
The paper deals with the description and results of long-term monitoring of thermal processes within the old coal dumps in Ostrava region. It presents methods and means of temperature measurements by specially installed temperature probes, including further wireless data transfer to dispatching center. The paper also discusses the possibility of creating predictive algorithm to predict changes of...
Many various algorithms are developed for state estimation of dynamic switching systems. It is not a straightforward task to choose the most suitable one. This paper deals with testing of state estimation via two well-known approaches: recursive estimation with finite mixtures and iterative technique with hidden Markov models. A discussion of comparison of these online and offline counterparts is...
In electricity grids current production has to meet usage at all times. Load curves show several load peaks during the day leading to problems for electricity providers. In this paper it is shown how to build load- and time-variable tariffs to obtain defined target load curves through demand response. Results show that total annual costs rise if load-reduction or peak-reduction target load curves...
A large amount of neurophysiological research is based on the study of biological neural populations. The data is gathered from extra-cellular recordings with multi-electrode arrays (MEAs). The signal is a stream containing an unknown number of neural sources superpositioned with non-stationary noise components. In order to analyze the recorded spike trains, a prior separation into its individual...
One of the major issues of monitoring activities in smart environments is the building of activity models from sensor's timed data. This paper proposes a general theoretical approach to this aim that provides operational results as it is illustrated with the prototypical home of the GerHome project. This proposal is based on the use of a Knowledge Engineering methodology and a Machine Learning process...
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