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EN
The paper presents a system which to make proper poker decision in situations provided by end user via image of the online poker table. The system provides feedback and reasoning behind decision made. The main goal is to minimize influences of errors and unwanted factors on each step so final decision could be accurate and useful in as many cases as possible. The idea is to use softcomputing technologies as neural networks for image recognition and expert system for decision making process. The system - able to parse poker table image - could be used by poker player for self-study on example on his/her own past in-game situations. Image is screenshot of the interface that is provided by online poker room to a player, so all information available to a player will also be available for further processing. The proposed solution can be an essential tool for the monitoring and verification of card game rules systems and to point the incorrect or illegal situations based on video data.
EN
The paper presents an approach to complex analysis of sophisticated Discrete Transport Systems (DTS) using softcomputing. The proposed methodology can efficiently substitute the classical approach especially since dependability parameters of the system are mostly approximated by experts instead of classical sources of data. On the other hand we can try to combine reliability and functional aspects. The paper describes the multicriteria scientific field of the Discrete Transport Systems and shows the way how the softcomputing can be in use in the sensible way. Moreover, results of the numerical experiment performed on a test case scenario related to the reliability and functional aspects using proposed methodology are given. The approach allows reducing the problem of assumptions of reliability distributions and – this way – seems to be very interesting for real systems management and tuning.
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