Search results for "technique de prévision"

showing 3 items of 3 documents

Modelling sensitive elasmobranchs habitat

2013

Basic information on the distribution and habitat preferences of ecologically important species is essential for their management and protection. In the Mediterranean Sea there is increasing concern over elasmobranch species because their biological (ecological) characteristics make them highly vulnerable to fishing pressure. Their removal could affect the structure and function of marine ecosystems, inducing changes in trophic interactions at the community level due to the selective elimination of predators or prey species, competitors and species replacement. In this study Bayesian hierarchical spatial models are used to map the sensitive habitats of the three most caught elasmobranch spe…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28840Etmopterus spinaxhabitatAquatic ScienceDistribution des populationshttp://aims.fao.org/aos/agrovoc/c_38371OceanographyGaleus melastomus010603 evolutionary biology01 natural sciencesElasmobranch habitatPredationMediterranean seahttp://aims.fao.org/aos/agrovoc/c_38127http://aims.fao.org/aos/agrovoc/c_3041Scyliorhinus caniculaMediterranean SeaVulnerable speciesMarine ecosystem14. Life underwaterhttp://aims.fao.org/aos/agrovoc/c_4699Ecology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_12399Trophic levelhttp://aims.fao.org/aos/agrovoc/c_6113biologyEcologyU10 - Informatique mathématiques et statistiques010604 marine biology & hydrobiologyScyliorhinus caniculabiology.organism_classificationBiologie marinetechnique de prévisionBayesian hierarchical spatial modelSpecies distribution modelingFisheryHabitatThéorie bayésienneGaleus melastomusM40 - Écologie aquatiquehttp://aims.fao.org/aos/agrovoc/c_10566http://aims.fao.org/aos/agrovoc/c_3456http://aims.fao.org/aos/agrovoc/c_38117Elasmobranchii
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Optimizing the level of service quality of a bike-sharing system

2016

Public bike-sharing programs have been deployed in hundreds of cities worldwide, improving mobility in a socially equitable and environmentally sustainable way. However, the quality of the service is drastically affected by imbalances in the distribution of bicycles among stations. We address this problem in two stages. First, we estimate the unsatisfied demand (lack of free lockers or lack of bicycles) at each station for a given time period in the future and for each possible number of bicycles at the beginning of the period. In a second stage, we use these estimates to guide our redistribution algorithms. Computational results using real data from the bike-sharing system in Palma de Mall…

Information Systems and ManagementOperations researchStrategy and Managementmedia_common.quotation_subject0211 other engineering and technologiesDistribution (economics)02 engineering and technologyManagement Science and Operations Researchhttp://aims.fao.org/aos/agrovoc/c_63329Transport engineeringhttp://aims.fao.org/aos/agrovoc/c_3041http://aims.fao.org/aos/agrovoc/c_7524http://aims.fao.org/aos/agrovoc/c_353320502 economics and businessserviceQuality (business)media_common050210 logistics & transportation021103 operations researchU10 - Informatique mathématiques et statistiquesLevel of servicebusiness.industry05 social sciencesRedistribution (cultural anthropology)Demand forecastingtechnique de prévisionhttp://aims.fao.org/aos/agrovoc/c_9000074BicyclettesOffre et demandehttp://aims.fao.org/aos/agrovoc/c_dda00d10Développement durableService (economics)http://aims.fao.org/aos/agrovoc/c_6989http://aims.fao.org/aos/agrovoc/c_7273Bike sharingapproches communautairesBusinessHeuristicsOmega
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Geostatistical computing of acoustic maps in the presence of barriers

2009

Acoustic maps are the main diagnostic tools used by authorities for addressing the growing problem of urban acoustic contamination. Geostatistics models phenomena with spatial variation, but restricted to homogeneous prediction regions. The presence of barriers such as buildings introduces discontinuities in prediction areas. In this paper we investigate how to incorporate information of a geographical nature into the process of geostatistical prediction. In addition, we study the use of a Cost-Based distance to quantify the correlation between locations.

acoustic mapsComputer sciencehttp://aims.fao.org/aos/agrovoc/c_8085non_euclidean geostatisticsClassification of discontinuities010502 geochemistry & geophysicsDiagnostic toolscomputer.software_genre01 natural scienceshttp://aims.fao.org/aos/agrovoc/c_35131acousticcomputational methods010104 statistics & probabilitySystème d'information géographique11. Sustainability[STAT.CO]Statistics [stat]/Computation [stat.CO]http://aims.fao.org/aos/agrovoc/c_98[STAT.AP]Statistics [stat]/Applications [stat.AP]mapshttp://aims.fao.org/aos/agrovoc/c_49911Propriété acoustiquetechnique de prévisionhttp://aims.fao.org/aos/agrovoc/c_ded17449B10 - GéographieComputer Science Applicationscost-Based distanceHomogeneousModeling and Simulationhttp://aims.fao.org/aos/agrovoc/c_7251Data miningGéostatistiques[STAT.ME]Statistics [stat]/Methodology [stat.ME]Zone urbaineSon (acoustique)Process (engineering)Geostatisticscost_surfacegiscomputinghttp://aims.fao.org/aos/agrovoc/c_3041Modelling and Simulationacoustiquegeostatistics0101 mathematics0105 earth and related environmental sciencesbusiness.industry[SDE.ES]Environmental Sciences/Environmental and SocietySpatial variabilityArtificial intelligenceU30 - Méthodes de recherchebusinesscomputerMathematical and Computer Modelling
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