Number of found documents: 1499
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Bayesian Networks for the Analysis of Subjective Well-Being
Švorc, Jan; Vomlel, Jiří
2019 - English
We use Bayesian Networks to model the influence of diverse socio-economic factors on subjective well-being and their interrelations. The classical statistical analysis aims at finding significant explanatory variables, while Bayesian Networks can also help sociologists to explain and visualize the problem in its complexity. Using Bayesian Networks the sociologists may get a deeper insight into the interplay of all measured factors and their influence on the variable of a special interest. In the paper we present several Bayesian Network models -- each being optimal from a different perspective. We show how important it is to pay a special attention to a local structure of conditional probability tables. Finally, we present results of an experimental evaluation of the suggested approaches based on real data from a large international survey. We believe that the suggested approach is well applicable to other sociological problems and that Bayesian Networks represent a new valuable tool for sociological research. Keywords: Bayesian networks; Subjective well-being Fulltext is available at external website.
Bayesian Networks for the Analysis of Subjective Well-Being

We use Bayesian Networks to model the influence of diverse socio-economic factors on subjective well-being and their interrelations. The classical statistical analysis aims at finding significant ...

Švorc, Jan; Vomlel, Jiří
Ústav teorie informace a automatizace, 2019

Application of the Cox regression model with time dependent parameters to unemployment data
Volf, Petr
2019 - English
The contribution deals with the application of statistical survival analysis with the intensity described by a generalized version of Cox regression model with time dependent parameters. A\nmethod of model components non-parametric estimation is recalled, the flexibility of result is assessed with a goodness-of-fit test based on martingale residuals. The application\nconcerns to the real data representing the job opportunities development and reduction, during a given period. The risk of leaving the company is changing in time and depends also on the age of employees and their time with company. Both these covariates are considered and their impact to the risk analyzed. Keywords: mathematical statistics; survival analysis; unemployment data Fulltext is available at external website.
Application of the Cox regression model with time dependent parameters to unemployment data

The contribution deals with the application of statistical survival analysis with the intensity described by a generalized version of Cox regression model with time dependent parameters. A\nmethod of ...

Volf, Petr
Ústav teorie informace a automatizace, 2019

A Robustified Metalearning Procedure for Regression Estimators
Kalina, Jan; Neoral, A.
2019 - English
Metalearning represents a useful methodology for selecting and recommending a suitable algorithm or method for a new dataset exploiting a database of training datasets. While metalearning is potentially beneficial for the analysis of economic data, we must be aware of its instability and sensitivity to outlying measurements (outliers) as well as measurement errors. The aim of this paper is to robustify the metalearning process. First, we prepare some useful theoretical tools exploiting the idea of implicit weighting, inspired by the least weighted squares estimator. These include a robust coefficient of determination, a robust version of mean square error, and a simple rule for outlier detection in linear regression. We perform a metalearning study for recommending the best linear regression estimator for a new dataset (not included in the training database). The prediction of the optimal estimator is learned over a set of 20 real datasets with economic motivation, while the least squares are compared with several (highly) robust estimators. We investigate the effect of variable selection on the metalearning results. If the training as well as validation data are considered after a proper robust variable selection, the metalearning performance is improved remarkably, especially if a robust prediction error is used. Keywords: model choice; computational statistics; robustness; variable selection Fulltext is available at external website.
A Robustified Metalearning Procedure for Regression Estimators

Metalearning represents a useful methodology for selecting and recommending a suitable algorithm or method for a new dataset exploiting a database of training datasets. While metalearning is ...

Kalina, Jan; Neoral, A.
Ústav teorie informace a automatizace, 2019

Balancing Exploitation and Exploration via Fully Probabilistic Design of Decision Policies
Kárný, Miroslav; Hůla, František
2018 - English
Adaptive decision making learns an environment model serving a design of a decision policy. The policy-generated actions influence both the acquired reward and the future knowledge. The optimal policy properly balances exploitation with exploration. The inherent dimensionality\ncurse of decision making under incomplete knowledge prevents the realisation of the optimal design. Keywords: Exploitation; Exploration; Bayesian estimation; Adaptive systems; Fully probabilistic design; Kullback-Leibler divergence; Decision policy; Markov decision process Fulltext is available at external website.
Balancing Exploitation and Exploration via Fully Probabilistic Design of Decision Policies

Adaptive decision making learns an environment model serving a design of a decision policy. The policy-generated actions influence both the acquired reward and the future knowledge. The optimal policy ...

Kárný, Miroslav; Hůla, František
Ústav teorie informace a automatizace, 2018

Adaptace programového vybavení pro hodnocení radiologických důsledků mimořádných úniků radionuklidů ze skladů vyhořelého jaderného paliva
Pecha, Petr; Pechová, E.
2018 - Czech
Revize implicitní grupy radionuklidů a rozšíření o typické postulované mimořádné úniky ze skladů vyhořelého paliva. bylo provedeno rozšíření databáze radionuklidů systému HARP o další nejdůležitější dlouhodobé radionuklidy. V zásadě se jednalo o výběr štěpných a aktivačních produktů a dále o transurany ze skupiny aktinidů. Jsou konstatovány velké neurčitosti v odhadech zdrojových členů úniku pro případy vyhořelého paliva. Je provedeno vzájemné srovnání pro obálkové scénáře s výsledky evropského environmentálního kódu COSYMA pro rozšířenou grupu transuranů.. Analysis of implicit group of radionuclides and its extension included nuclides with long half-llive of decay. Selection from spent fuel inventories. Selection from fision products, transurans an actinide group. Estimation of possible uncertainties. Comparison analysis is done betřween HARP and European COSYMA codes. Keywords: Spent fuel; discharges from repository; radiological impact Fulltext is available at external website.
Adaptace programového vybavení pro hodnocení radiologických důsledků mimořádných úniků radionuklidů ze skladů vyhořelého jaderného paliva

Revize implicitní grupy radionuklidů a rozšíření o typické postulované mimořádné úniky ze skladů vyhořelého paliva. bylo provedeno rozšíření databáze radionuklidů systému HARP o další nejdůležitější ...

Pecha, Petr; Pechová, E.
Ústav teorie informace a automatizace, 2018

Validation of comprehensive energy management system based on cloud-sourced information
Nedoma, P.; Herda, Z.; Franc, Z.; Plíhal, Jiří
2018 - English
The main research activity was devoted to develop an application that would enable testing interface between OIKOS board (based on the AURIXTM) and the dissemination module represented by Skoda vehicle demonstrator through serial port RS232. The testing was based on sending the GPS coordinates to the OIKOS unit and receiving recommended speed profile for the given track. While dissemination unit has received GPS coordinates, AURIX chip has sent back messages with prediction of possible speed profile. Further tasks included verification other forms of transmission, such as Wi-Fi, Bluetooth, Ethernet.\n\n Keywords: OIKOS board; dissemination module; GPS Fulltext is available at external website.
Validation of comprehensive energy management system based on cloud-sourced information

The main research activity was devoted to develop an application that would enable testing interface between OIKOS board (based on the AURIXTM) and the dissemination module represented by Skoda ...

Nedoma, P.; Herda, Z.; Franc, Z.; Plíhal, Jiří
Ústav teorie informace a automatizace, 2018

Automatizovaný softwarový systém pro logopedickou terapii
Paroubková, M.; Bílková, Zuzana; Novozámský, Adam; Dominec, A.; Zitová, Barbara
2018 - Czech
Představení automatizovaného softwarového systému pro logopedickou terapii dětí i dospělých (Assistl). Introduction of an automated software system for speech therapy of children and adults (Assistl). Keywords: speech therapy; tongue; motor speech disorders Fulltext is available at external website.
Automatizovaný softwarový systém pro logopedickou terapii

Představení automatizovaného softwarového systému pro logopedickou terapii dětí i dospělých (Assistl)....

Paroubková, M.; Bílková, Zuzana; Novozámský, Adam; Dominec, A.; Zitová, Barbara
Ústav teorie informace a automatizace, 2018

Experiment: Cooperative Decision Making via Reinforcement Learning
Berka, Milan
2018 - English
This report inspects cooperative decision making task using reinforcement learning. It serves for comparison with methodology based on fully probabilistic design of decision strategies. Keywords: decision making; reinforcement learning; cooperation Fulltext is available at external website.
Experiment: Cooperative Decision Making via Reinforcement Learning

This report inspects cooperative decision making task using reinforcement learning. It serves for comparison with methodology based on fully probabilistic design of decision strategies.

Berka, Milan
Ústav teorie informace a automatizace, 2018

Heuristics in blind source separation
Kautský, Václav; Štěch, Jakub
2018 - English
This paper deals with application of heuristic algorithms (DEBR, MCRS) in blind source separation (BSS). BSS methods focus on a separation of the (source) signal from a linear mixture. The idea of using heuristic algorithms is introduced on the independent component extraction (ICE) model. The motivation for considering heuristics is to obtain an initial guess needed by many ICE algorithms. Moreover, the comparison of this initialization, and other algorithms accuracy is performed.\n Keywords: Blind Source Separation; DEBR; Independent Component Extraction Fulltext is available at external website.
Heuristics in blind source separation

This paper deals with application of heuristic algorithms (DEBR, MCRS) in blind source separation (BSS). BSS methods focus on a separation of the (source) signal from a linear mixture. The idea of ...

Kautský, Václav; Štěch, Jakub
Ústav teorie informace a automatizace, 2018

Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems
Šmíd, Martin; Kozmík, Václav
2018 - English
Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, Coin-OR, APML or, for smaller problems, Excel), it is, however, mostly up to researcher to reformulate the problem into its deterministic equivalent. Moreover, such solutions are usually one-time, not easy to modify for different applications. We overcome these problems by providing a front-end software package, written in C++, which enables to enter problem definitions in a way close to their mathematical definition. Creating of a deterministic equivalent (and its solution) is up to the computer. In particular, our code is able to solve linear multi-stage with Multi-period Mean-CVaR or Nested Mean-CVaR criteria. In the present paper, we describe the algorithms, transforming these problems into their deterministic equivalents. Keywords: Multi-stage stochastic programming; deterministic equivalent; multi-period CVaR; nested CVaR; optimization algorithm Fulltext is available at external website.
Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems

Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, ...

Šmíd, Martin; Kozmík, Václav
Ústav teorie informace a automatizace, 2018

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