Data mining for performance of vegetative filter strips

Language: English

Published by LAP LAMBERT Academic Publishing Dez 2013, 2013

365950615X / 9783659506154

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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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 216 pp. Englisch.

Seller Inventory # 9783659506154

Title
Data mining for performance of vegetative filter strips
Author
Sanyogita Andriyas
Publisher
LAP LAMBERT Academic Publishing Dez 2013
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
365950615X
ISBN 13
9783659506154
Item weight
340 grams
Dimensions
220x150x14 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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