Wyniki wyszukiwania - BazTech

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Primary development directions for a network of art centres in Ukraine

Kostiuchenko Olha

Przestrzeń i Forma

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2020

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nr 41

35--42

EN

The article analyses the development directions of architectural thought with regard to establishment of art centres on the territory of Ukraine. It is established that existing national art centres are located in integrated premises and need improvement. The article emphasize the necessity of holistic development of a modern network of art centres in Ukraine based on developed conceptual models.

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Learning structures of conceptual models from observed dynamics using evolutionary echo state networks

Abdelbari H., Shafi K.

Journal of Artificial Intelligence and Soft Computing Research

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2018

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Vol. 8, No. 2

133--154

EN

Conceptual or explanatory models are a key element in the process of complex system modelling. They not only provide an intuitive way for modellers to comprehend and scope the complex phenomena under investigation through an abstract representation but also pave the way for the later development of detailed and higher-resolution simulation models. An evolutionary echo state network-based method for supporting the development of such models, which can help to expedite the generation of alternative models for explaining the underlying phenomena and potentially reduce the manual effort required, is proposed. It relies on a customised echo state neural network for learning sparse conceptual model representations from the observed data. In this paper, three evolutionary algorithms, a genetic algorithm, differential evolution and particle swarm optimisation are applied to optimize the network design in order to improve model learning. The proposed methodology is tested on four examples of problems that represent complex system models in the economic, ecological and physical domains. The empirical analysis shows that the proposed technique can learn models which are both sparse and effective for generating the output that matches the observed behaviour.

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Aktualne problemy automatycznej generalizacji danych przestrzennych

Karsznia I.

Polski Przegląd Kartograficzny

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2009

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T. 41, nr 1

5-16

PL

W artykule opisano podstawowe założenia procesu generalizacji danych przestrzennych. Scharakteryzowano ważniejsze modele konceptualne generalizacji oraz metody optymalizacji i kontroli tego procesu. Następnie nakreślono aktualne problemy i kierunki badań, jakimi są m.in. kontekstowość procesu generalizacji, generalizacja on-line i wieloreprezentacyjne bazy danych przestrzennych, holistyczny charakter procesu generalizacji, możliwości formalizacji wiedzy kartograficznej oraz opracowanie wspólnej platformy generalizacyjnej.

EN

Generalization is one of basic features of cartographic presentation. According to the International Cartographic Association generalization is a seleetion and simplification of geographic information to fit the map's scale and purpose. In the 80s and 90s the research on automation of the generalization process focused on two major issues: development of new generalization algorithms and acquisition and application of cartographic knowledge, eg. in the form of rules in expert systems. Nowadays research concentrates firstly on more comprehensive generalization algorithms, accounting for a series of factors and spatial relations between objects, and secondly on more advanced generalization techniques, e.g. multi agent systems. Dynamic development of research on generalization automation raised the requirements for the already existing or currently developed systems supporting the process of generalization. The research focuses on: - acquisition of cartographic knowledge in order to identify the rules which govern the process of generalization, - formalization of the rules of generalization, - development of generalization models, - development of more comprehensive tools for spatial analysis and new generalization algorithms, - modeling of geographic space in the form of object-oriented structures, with fuller geometrie and topologie features of spatial data, attempts to apply algorithms and data structures which support the process of cartographic generalization (e.g. application of Delauney's triangulation in the process of building relocation), - elaboration of multi-representational spatial data-bases, enabling the user to visualize data from one base on different levels of detail, - possibility to apply the available generalization algorithms in a selected software environment in order to experiment with the application sequence and harmonization. The article discusses basic assumptions of the process of spatial data generalization. More important conceptual models of generalization and methods of optimization and control of the process are characterized. Current problems and research direetions are presented, with special attention being paid to: contextual aspects of the generalization process, on-line generalization, multi-presentational spatial databases, comprehensive character of the process, possibility to formalize cartographic knowledge and development of a common generalization platform.