Articles liés à Data mining for performance of vegetative filter strips:...
Data mining for performance of vegetative filter strips: A comparison between prediction models : artificial neural networks (back propagation & radial basis function) vs. GRAPH - Couverture souple
Synopsis
The vegetative filter strips (VFS) are a best management practice. For quantifying the movement & amount of sediments & nutrients, the performance of VFS has to be modeled. Data available from the literature & recent experiments were used. Artificial runoff was created. Flow samples were analysed for concentrations for total suspended solids, total phosphorus & soluble phosphorus, & particle size distribution. Input-output data sets were used to train & test a multi-layered perceptron using back propagation (BP) algorithm & a radial basis function neural network using fuzzy c-means clustering algorithm. Sensitivity tests were done for finding optimum architectures of neural networks. The statistical analysis & comparisons between predicted & observed values for the three models showed that a BP network with 15 hidden units can model the performance of VFS efficiently, including the trapping of soluble P. They could predict the outputs, even without the particle size distribution. ANN'S have to be trained before being used to predict the outputs. GRAPH is mobile & could be successfully used for verification, since it takes into account the physical processes going on.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Présentation de l'éditeur
The vegetative filter strips (VFS) are a best management practice. For quantifying the movement & amount of sediments & nutrients, the performance of VFS has to be modeled. Data available from the literature & recent experiments were used. Artificial runoff was created. Flow samples were analysed for concentrations for total suspended solids, total phosphorus & soluble phosphorus, & particle size distribution. Input-output data sets were used to train & test a multi-layered perceptron using back propagation (BP) algorithm & a radial basis function neural network using fuzzy c-means clustering algorithm. Sensitivity tests were done for finding optimum architectures of neural networks. The statistical analysis & comparisons between predicted & observed values for the three models showed that a BP network with 15 hidden units can model the performance of VFS efficiently, including the trapping of soluble P. They could predict the outputs, even without the particle size distribution. ANN'S have to be trained before being used to predict the outputs. GRAPH is mobile & could be successfully used for verification, since it takes into account the physical processes going on.
Biographie de l'auteur
I have an expertise in machine learning techniques and their application in the field of water resources engineering and management.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurLAP LAMBERT Academic Publishing
- Date d'édition2013
- ISBN 10 365950615X
- ISBN 13 9783659506154
- ReliureBroché
- Langueanglais
- Nombre de pages216
- Coordonnées du fabricantnon disponible
Acheter neuf
Afficher cet article
EUR 61,85
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisRésultats de recherche pour Data mining for performance of vegetative filter strips:...
Image fournie par le vendeur
Data mining for performance of vegetative filter strips
Edité par
LAP LAMBERT Academic Publishing, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Andriyas SanyogitaI have an expertise in machine learning techniques and their application in the field of water resources engineering and management.The vegetative filter strips (VFS) are a best management practice. For quantify. N° de réf. du vendeur 5160858
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Data mining for performance of vegetative filter strips
Edité par
LAP LAMBERT Academic Publishing Dez 2013, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The vegetative filter strips (VFS) are a best management practice. For quantifying the movement & amount of sediments & nutrients, the performance of VFS has to be modeled. Data available from the literature & recent experiments were used. Artificial runoff was created. Flow samples were analysed for concentrations for total suspended solids, total phosphorus & soluble phosphorus, & particle size distribution. Input-output data sets were used to train & test a multi-layered perceptron using back propagation (BP) algorithm & a radial basis function neural network using fuzzy c-means clustering algorithm. Sensitivity tests were done for finding optimum architectures of neural networks. The statistical analysis & comparisons between predicted & observed values for the three models showed that a BP network with 15 hidden units can model the performance of VFS efficiently, including the trapping of soluble P. They could predict the outputs, even without the particle size distribution. ANN'S have to be trained before being used to predict the outputs. GRAPH is mobile & could be successfully used for verification, since it takes into account the physical processes going on. 216 pp. Englisch. N° de réf. du vendeur 9783659506154
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Data mining for performance of vegetative filter strips : A comparison between prediction models : artificial neural networks (back propagation & radial basis function) vs. GRAPH
Edité par
LAP LAMBERT Academic Publishing, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The vegetative filter strips (VFS) are a best management practice. For quantifying the movement & amount of sediments & nutrients, the performance of VFS has to be modeled. Data available from the literature & recent experiments were used. Artificial runoff was created. Flow samples were analysed for concentrations for total suspended solids, total phosphorus & soluble phosphorus, & particle size distribution. Input-output data sets were used to train & test a multi-layered perceptron using back propagation (BP) algorithm & a radial basis function neural network using fuzzy c-means clustering algorithm. Sensitivity tests were done for finding optimum architectures of neural networks. The statistical analysis & comparisons between predicted & observed values for the three models showed that a BP network with 15 hidden units can model the performance of VFS efficiently, including the trapping of soluble P. They could predict the outputs, even without the particle size distribution. ANN'S have to be trained before being used to predict the outputs. GRAPH is mobile & could be successfully used for verification, since it takes into account the physical processes going on. N° de réf. du vendeur 9783659506154
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Data mining for performance of vegetative filter strips
Edité par
LAP LAMBERT Academic Publishing Dez 2013, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The vegetative filter strips (VFS) are a best management practice. For quantifying the movement & amount of sediments & nutrients, the performance of VFS has to be modeled. Data available from the literature & recent experiments were used. Artificial runoff was created. Flow samples were analysed for concentrations for total suspended solids, total phosphorus & soluble phosphorus, & particle size distribution. Input-output data sets were used to train & test a multi-layered perceptron using back propagation (BP) algorithm & a radial basis function neural network using fuzzy c-means clustering algorithm. Sensitivity tests were done for finding optimum architectures of neural networks. The statistical analysis & comparisons between predicted & observed values for the three models showed that a BP network with 15 hidden units can model the performance of VFS efficiently, including the trapping of soluble P. They could predict the outputs, even without the particle size distribution. ANN'S have to be trained before being used to predict the outputs. GRAPH is mobile & could be successfully used for verification, since it takes into account the physical processes going on.Books on Demand GmbH, Überseering 33, 22297 Hamburg 216 pp. Englisch. N° de réf. du vendeur 9783659506154
Quantité disponible : 1 disponible(s)
Image d'archives
Data mining for performance of vegetative filter strips
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Couverture souple
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. pp. 216. N° de réf. du vendeur 26127582614
Quantité disponible : 4 disponible(s)
Image d'archives
Data mining for performance of vegetative filter strips
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Couverture souple
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Print on Demand pp. 216 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. N° de réf. du vendeur 133004873
Quantité disponible : 4 disponible(s)
Image d'archives
Data mining for performance of vegetative filter strips
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
ISBN 10 : 365950615X
ISBN 13 : 9783659506154
Neuf
Couverture souple
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. PRINT ON DEMAND pp. 216. N° de réf. du vendeur 18127582620
Quantité disponible : 4 disponible(s)