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Artificial neural network onto eight bit microcontroller for Secchi depth calculation

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Artificial neural network onto eight bit microcontroller for Secchi depth calculation

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dc.contributor.author Ibáñez Civera, Francisco Javier es_ES
dc.contributor.author García Breijo, Eduardo es_ES
dc.contributor.author Laguarda Miró, Nicolás es_ES
dc.contributor.author Gil Sánchez, Luís es_ES
dc.contributor.author Garrigues Baixauli, José es_ES
dc.contributor.author Romero Gil, Inmaculada es_ES
dc.contributor.author Masot Peris, Rafael es_ES
dc.contributor.author Alcañiz Fillol, Miguel es_ES
dc.date.accessioned 2015-02-13T11:39:53Z
dc.date.available 2015-02-13T11:39:53Z
dc.date.issued 2011-08-10
dc.identifier.issn 0925-4005
dc.identifier.uri http://hdl.handle.net/10251/47017
dc.description.abstract In this paper we present a model to predict Secchi depth in water bodies by means of an artificial neural network application onto eight bit microcontroller. Water turbidity data were collected by both a Secchi disk and a new patented device (named LUZEX) that uses commercial photodiodes with not monochromatic sensitive band as a basis to perform "in situ" measurements for sunlight extinction coefficients. In order to have a wide range of turbidity data three different water bodies were selected to do the measurements. The developed neural network model is able to relate well the data obtained by these methods and the obtained value for regression coefficient (R) is 0.998. Secchi depth measure is a reference method to determine turbidity in continental and coastal water bodies, especially in the Mediterranean Sea region, but sometimes there are particular cases that makes difficult the use of the Secchi disk (e.g. shallow water bodies), the authors propose LUZEX as a substitute for Secchi disk when it is difficult or impossible to use. © 2011 Elsevier B.V. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Sensors and Actuators B: Chemical es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Artificial neural network es_ES
dc.subject Secchi depth es_ES
dc.subject Secchi disk es_ES
dc.subject Sunlight extinction coefficient es_ES
dc.subject Turbidity es_ES
dc.subject Water quality es_ES
dc.subject Coastal water bodies es_ES
dc.subject Commercial photodiodes es_ES
dc.subject Extinction coefficients es_ES
dc.subject In-situ es_ES
dc.subject Mediterranean sea es_ES
dc.subject Neural network model es_ES
dc.subject Reference method es_ES
dc.subject Regression coefficient es_ES
dc.subject Shallow water bodies es_ES
dc.subject Water turbidity es_ES
dc.subject Waterbodies es_ES
dc.subject Microcontrollers es_ES
dc.subject Water analysis es_ES
dc.subject Neural networks es_ES
dc.subject.classification INGENIERIA QUIMICA es_ES
dc.subject.classification TECNOLOGIA DEL MEDIO AMBIENTE es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Artificial neural network onto eight bit microcontroller for Secchi depth calculation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.snb.2011.04.001
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Química y Nuclear - Departament d'Enginyeria Química i Nuclear es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Reconocimiento Molecular y Desarrollo Tecnológico - Institut de Reconeixement Molecular i Desenvolupament Tecnològic es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient es_ES
dc.description.bibliographicCitation Ibáñez Civera, FJ.; García Breijo, E.; Laguarda Miró, N.; Gil Sánchez, L.; Garrigues Baixauli, J.; Romero Gil, I.; Masot Peris, R.... (2011). Artificial neural network onto eight bit microcontroller for Secchi depth calculation. Sensors and Actuators B: Chemical. 156(1):132-139. doi:10.1016/j.snb.2011.04.001 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.snb.2011.04.001 es_ES
dc.description.upvformatpinicio 132 es_ES
dc.description.upvformatpfin 139 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 156 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 198368


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