Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/52072
Título: | Advantages of model driven engineering for studying complex systems | Autores/as: | Évora Gómez, José Hernández Cabrera, José Juan Hernandez, Mario |
Clasificación UNESCO: | 120304 Inteligencia artificial | Palabras clave: | Agent based model Electrical system Domestic load curve simulation Residential demand Demand side management, et al. |
Fecha de publicación: | 2015 | Proyectos: | Framework Para la Simulación de la Gestión de Mercado y Técnica de Redes Eléctricas Insulares Basado en Agentes Inteligentes. Caso de la Red Eléctrica de Gran Canaria. | Publicación seriada: | Natural Computing | Resumen: | The evaluation of the emergent behaviour in complex systems requires an analytical framework which allows the observation of different phenomena that take place at different levels. In order to observe the dynamics of complex systems, it is necessary to perform simulations so that both local and the emergent behaviour can be observed. To this end, the way in which complex system simulators are built must be examined so that it will be feasible to model large scale scenarios. In this paper, the use of Model Driven Engineering methodology is proposed to deal with this issue. Among other benefits, it is shown that this methodology allows the representation and simulation of a complex system providing support for the analysis. This analysis is supported by a metamodel which describes the system components that are under study. The application of this methodology to the development of large scale simulators is explored through a case study. This case study analyses a complex socio-technical system: a power grid. | URI: | http://hdl.handle.net/10553/52072 | ISSN: | 1567-7818 | DOI: | 10.1007/s11047-014-9469-y | Fuente: | Natural Computing [ISSN 1567-7818], v. 14 (1), p. 129-144 |
Colección: | Artículos |
Citas SCOPUSTM
5
actualizado el 17-nov-2024
Citas de WEB OF SCIENCETM
Citations
5
actualizado el 17-nov-2024
Visitas
138
actualizado el 28-sep-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.