Listar por autor "Photis, Y. N."
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Analyzing High-Risk Emergency Areas with GIS and Neural Networks: The Case of Athens, Greece
Grekousis, G.; Photis, Y. N. (2014)Any analysis of health service problems facing the world today must consider that these problems exist in a geographic context. This fact has led to an increased need for accurate and current information to support emergency ... -
Erratum to: A fuzzy index for detecting spatiotemporal outliers (Geoinformatica, (2011), 10.1007/s10707-011-0145-4)
Grekousis, G.; Photis, Y. N. (2012) -
Locational planning for emergency management and response: An artificial intelligence approach
Photis, Y. N.; Grekousis, G. (2012)The efficiency of emergency service systems is measured in terms of their ability to deploy units and personnel in a timely and effective manner upon an event's occurrence. When dealing with public sector institutions, ... -
Measuring urban concentration: A spatial cluster typology based on public and private sector service patterns
Tsompanoglou, S.; Photis, Y. N. (2013)The main objective of this paper is the definition of a methodological framework for the determination, analysis and cross-evaluation of urban clusters which are formulated within wider study areas, such as administrative ... -
Modeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area
Grekousis, G.; Manetos, P.; Photis, Y. N. (2013)This paper presents an artificial intelligence approach integrated with geographical information systems (GISs) for modeling urban evolution. Fuzzy logic and neural networks are used to provide a synthetic spatiotemporal ...