Estimación de temperatura y humedad relativa en Venezuela mediante redes neuronales

dc.contributor.authorLuis Armando Rosario Moreno
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T16:07:13Z
dc.date.available2026-03-22T16:07:13Z
dc.date.issued2001
dc.descriptionCitaciones: 1
dc.description.abstractThe aim of this paper is to present estimations about climatic conditions in Venezuela by using a neural network model. These conditions include values of dry-bulb temperature, relative humidity based on a yearly average. These values are calculated using the altitude and the geographical localization. The estimates were carried out by using an annual average, from 1989 to1998, in various locations taken from weather stations that belong to the Fuerza Aerea Venezolana. This information is commonly used for design, sizing, distribution, installation, and marketing air-conditioning equipment; as well as for other energy-related processes in residential, agricultural, commercial and industrial applications.
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/56357
dc.language.isoes
dc.sourceUniversidad de Los Andes
dc.subjectDry-bulb temperature
dc.subjectAltitude (triangle)
dc.subjectEnvironmental science
dc.subjectWet-bulb temperature
dc.subjectRelative humidity
dc.subjectGeography
dc.subjectAir temperature
dc.subjectMeteorology
dc.subjectForestry
dc.subjectHumidity
dc.titleEstimación de temperatura y humedad relativa en Venezuela mediante redes neuronales
dc.typearticle

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