Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/45878
Title: Expert sistem for making decisions about emergency and safety in case of adverse meteorological conditions
Other Titles: Sistema experto para tomar decisiones de emergencias y seguridad ante meteorología adversa
Authors: Santacreu Ríos, Luis Juan 
Talavera-Ortiz, Alejandro 
Aguasca-Colomo, Ricardo 
Galván-González, Blas José 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Fenómeno Meteorológico Adverso
Sistema Experto
Inteligencia artificial
Proceso Analítico Jerárquico (AHP)
Lógica difusa
Issue Date: 2015
Journal: Dyna (Bilbao) 
Abstract: The volume of information used in the Emergency Coordination Center (1-1-2 CECOES), which depends on the Canary Government, during and after any adverse weather phenomenon (FMA in Spanish) is now significantly greater than before, The amount of bulletins warnings and forecasts about FMA sent by the Meteorological Agency (AEMET), and received at the 1-1-2 CECOES, is really considerable. The information should be treated as soon as possible in order to generate the corresponding pre-alerts and notifications, as well as public notices to the citizens The rule-based expert systems can overcome the human capacity, for example, when required to analyze a large volume of data in a limited period of time, as in the emergency services. Moreover, Fuzzy Logic is an artificial intelligence methodology that is effective when dealing with vagueness or ambiguity, erroneous or absence of information, something that the emergency services are used to: for example, "It rains a lot", "the storm is far away", " it is windy" and "we have low temperatures" , are typical responses given by some callers when they alert 1-1-2. Finally, Weather Forecasts usually work with imprecise concepts such as: possibility, (when the probability that a weather phenomenon occurs is between 10 and 40%) and probability, (when between 40 and 70%). We have primarily developed an expert helping-system for decision-making based on an inference engine implemented with Fuzzy Logic in CECOES 1-1-2. This system is able to provide clear answers at the inaccuracy or lack of information, and if trained with real cases, it can improve human behaviour giving a quick and effective response. Keywords: CECOES 1-1-2, Adverse Weather Phenomena, Expert System, Artificial Intelligence, Fuzzy Logic, Analytic Hierarchy Process (AHP).
URI: http://hdl.handle.net/10553/45878
ISSN: 0012-7361
DOI: 10.6036/7469
Source: Dyna (Bilbao) [ISSN 0012-7361], v. 90 (5), p. 503-512
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