Process Neural Network Models (3 results)
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Seller: liu xing, Nanjing, JS, Chinaliu xing
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paperback. Condition: New. Language:Chinese.Pub Date: 2014-04-01 Pages: 305 Publisher: National Defense Industry Press process neural network model and its engineering applications. will focus on wavelet process neural networks. the propagation neural network. Elman neural feedback process type Networks and double parallel proce…ss neural network model. discuss their learning algorithm. described in its generalization and application of technology. and aero-engine health management. for example. describes the process of.
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Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Hydrological Modelling using Process based and Data Driven Models | Process-based and Neural Network Modelling in Hydrology | Ajai Singh (u. a.) | Taschenbuch | 268 S. | Englisch | 2013 | Scholars' Press | EAN 9783639511079 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landst…r. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Point source pollution is relatively easily controllable and identifiable. Pollutants detected in a concentrated water source such as stream, river or lake are called non-point source pollution. Sedimentation and deteriorating water qual…ity due to non-point source pollution are nowadays a very serious problem in reservoirs, lakes and rivers and is caused by high discharges of nutrients and sediment from upstream river basins. Minimization of the discharges and improvement of the agricultural practices are the obvious solution of the problem. The application of various hydrological models helps the planners and water resource managers to plan appropriately to implement effective measures. In the present study, process-based Soil and Water Assessment Tool (SWAT) and artificial neural network models such as Multi-Layer Perceptron (MLP) and Radial Basis Neural Network (RBNN) have been applied to simulate hydrological processes such as stream flow and sediment yield on monthly time steps in agricultural watershed in Eastern India. The model outputs are compared in terms of well laid out statistical criterion.
