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Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain)

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Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain)

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dc.contributor.author de Domingo, Miguel es_ES
dc.contributor.author Ortigosa, Nuria es_ES
dc.contributor.author Sevilla, Javier es_ES
dc.contributor.author Roger, Sandra es_ES
dc.date.accessioned 2024-02-19T19:00:58Z
dc.date.available 2024-02-19T19:00:58Z
dc.date.issued 2021-02 es_ES
dc.identifier.uri http://hdl.handle.net/10251/202714
dc.description.abstract [EN] Forest fires are undesirable situations with tremendous impacts on wildlife and people's lives. Reaching them quickly is essential to slowing down their expansion and putting them out in an effective manner. This work proposes an optimized distribution of fire stations in the province of Valencia (Spain) to minimize the impacts of forest fires. Using historical data about fires in the Valencia province, together with the location information about existing fire stations and municipalities, two different clustering techniques have been applied. Floyd-Warshall dynamic programming algorithm has been used to estimate the average times to reach fires among municipalities and fire stations in order to quantify the impacts of station relocation. The minimization was done approximately through k-means clustering. The outcomes with different numbers of clusters determined a predicted tradeoff between reducing the time and the cost of more stations. The results show that the proposed relocation of fire stations generally ensures faster arrival to the municipalities compared to the current disposition of fire stations. In addition, deployment costs associated with station relocation are also of paramount importance, so this factor was also taken into account in the proposed approach. es_ES
dc.description.sponsorship Sandra Roger would like to thank the Spanish Ministry of Science, Innovation and Universities (RYC-2017-22101 Grant), and the Generalitat Valenciana (GV/2020/046 Project). Nuria Ortigosa acknowledges the support from Generalitat Valenciana (Prometeo/2017/102), and from Spanish MINECO (MTM2016-76647-P). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Fire prevention es_ES
dc.subject Artificial intelligence es_ES
dc.subject K-means es_ES
dc.subject DBSCAN,Floyd-Warshall es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain) es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s21030797 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//GV%2F2020%2F046 / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2017%2F102//ANALISIS FUNCIONAL, TEORIA DE OPERADORES Y APLICACIONES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MCIU//RYC-2017-22101/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//MTM2016-76647-P//Análisis funcional, teoría de operadores y análisis tiempo-frecuencia/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation De Domingo, M.; Ortigosa, N.; Sevilla, J.; Roger, S. (2021). Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain). Sensors. 21(3). https://doi.org/10.3390/s21030797 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/s21030797 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 21 es_ES
dc.description.issue 3 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 33504117 es_ES
dc.identifier.pmcid PMC7865265 es_ES
dc.relation.pasarela S\433711 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades es_ES


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