Titlebook: Computational and Statistical Methods in Intelligent Systems; Radek Silhavy,Petr Silhavy,Zdenka Prokopova Conference proceedings 2019 Spri

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Synchronization in Oscillatory Networksd to investments in real estate business. In this scenario, we perceive the need to identify and classify the attributes for a strategic investment decision, through a multicriteria decision model that allows greater economic effectiveness, considering a limited rationality from managers and their c

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Chains of Limit-Cycle Oscillatorsauthor proposes a new experimental method for patternizing syntactic structures of Vietnamese complex sentences. Specifically, 6 general structure classes for Vietnamese complex sentences have been patternized. After building and testing, the system is shown to have an accuracy of 82%–100%.

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Synchronization in Oscillatory Networkss is on possible methods for communities monitoring using the data of online social networks. The main research question is whether it is possible to investigate the real territorial characteristics of communities on the basis of their representations in a virtual environment? How accurately does th

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Chains of Limit-Cycle Oscillators very complex task can be rather effectively solved in case when consideration is limited by certain specific kind of texts. The paper describes the developed technology of extraction of deontological statements from legal acts through a multilevel analysis of text documents combining linguistic and

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https://doi.org/10.1007/978-3-540-71269-5 Department of Geoinformatics, Palacky University in Olomouc (Czech Republic). The Department of Geoinformatics has been running a continuous and systematic information campaign about studying the fields of geoinformatics and geography within the department. In order to collect feedback about the in

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Synchronization in Oscillatory Networksional data. In this paper we propose a similarity metric based feature selection method named .. We use the Euclidean distance to measure the similarity among all features, and then apply the density based DBSCAN algorithm to clustering features which to be relevant. Moreover, we present a strategy

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