Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10662/21083
Títulos: A fuzzy cognitive map-based algorithm for predicting water consumption in Spanish healthcare centres
Autores/as: Sánchez-Barroso Moreno, Gonzalo
González Domínguez, Jaime
Fernandes, Joao Paulo Almeida
García Sanz-Calcedo, Justo
Palabras clave: Water consumption;Fuzzy cognitive maps;Healthcare centres;Healthcare engineering;Water management;Consumo de agua;Mapas cognitivos difusos;Centros de salud;Ingeniería sanitaria;Administracion del Agua
Fecha de publicación: 2023
Editor/a: Springer
Resumen: The management of water consumption in healthcare centres can have positive impacts on both the environmental performance and profitability of health systems. Computational tools assist in the decision-making process of managing the operation and maintenance of healthcare centres. This research aimed to integrate the empirical knowledge of experts in Healthcare Engineering and the historical data from 66 healthcare centres in a Fuzzy Cognitive Map. The outputs of the predictive model included water consumption, water cost, and CO2 emissions in healthcare facilities, along with eleven variables to discover the causes and consequences of water consumption in healthcare centres. A healthcare centre with about 12 350 users, located in a city that experiences an average of 1100 heating degree days, whose facilities be moderately energy-efficient contributing over 50% with renewable energies is expected to consume 8.4 dam3 of water with 32.1 k€ of cost, and contribute realising 30.8 ton CO2eq emissions. The use of Fuzzy Cognitive Maps for prediction can provide a high level of effectiveness in identifying the factors that contribute to water consumption and in designing key performance indicators to manage the environmental performance of healthcare buildings. This tool is extremely effective in enhancing the performance of the management division of health systems.
Descripción: Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.
URI: http://hdl.handle.net/10662/21083
ISSN: 1996-3599
DOI: 10.1007/s12273-023-1028-y
Colección:DEXGR - Artículos

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