9783330041622 - application of artificial neural networks for predicting water quality di zaqoot, hossam; aish, adnan; abdeljawad, samaher (9 risultati)

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    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: Books Puddle, New York, NY, U.S.A.Books Puddle

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      Condizione: New.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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      Paperback. Condizione: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: preigu, Osnabrück, Germaniapreigu

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      Taschenbuch. Condizione: Neu. Application of Artificial Neural Networks for Predicting Water Quality | Hossam Zaqoot (u. a.) | Taschenbuch | 88 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330041622 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Lingua: Inglese

      Editore: LAP Lambert Academic Publishing Feb 2017, 2017

      3330041625 / 9783330041622

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      • Print on Demand

      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the Gaza Strip the maximum amount of the drinking water is produced through small private desalination plants. The present book is concerned with using artificial neural network (ANN) technique to forecast and predict the next week concentrations of total dissolved solids (TDS), chloride, nitrate and magnesium of the product water quality in the reverse osmosis desalination plants in the Gaza Strip. Multilayer perceptron (MLP) and radial basis function (RBF) neural networks were trained and developed with reference to product water parameters including: water temperature, pressure, pH and conductivity to predict TDS, chloride and nitrate next week values. MLP and RBF neural networks were trained and developed with reference to three water quality parameters including pressure, chloride and conductivity to predict magnesium concentrations. The prediction results showed that both types of neural networks are good for predicting TDS, chloride and nitrate levels and satisfactory for predicting magnesium.Results of both developed networks were compared with the statistical model and found that ANN predictions are better than the conventional methods. 88 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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      Condizione: New. Print on Demand.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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      Condizione: New. PRINT ON DEMAND.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: moluna, Greven, Germaniamoluna

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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zaqoot HossamAuthors have experience in projects managing and coordination in the field of water quality assessment and water quality modeling using artificial neural network, in addition to consultation and evaluation of research wo.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Feb 2017, 2017

      3330041625 / 9783330041622

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In the Gaza Strip the maximum amount of the drinking water is produced through small private desalination plants. The present book is concerned with using artificial neural network (ANN) technique to forecast and predict the next week concentrations of total dissolved solids (TDS), chloride, nitrate and magnesium of the product water quality in the reverse osmosis desalination plants in the Gaza Strip. Multilayer perceptron (MLP) and radial basis function (RBF) neural networks were trained and developed with reference to product water parameters including: water temperature, pressure, pH and conductivity to predict TDS, chloride and nitrate next week values. MLP and RBF neural networks were trained and developed with reference to three water quality parameters including pressure, chloride and conductivity to predict magnesium concentrations. The prediction results showed that both types of neural networks are good for predicting TDS, chloride and nitrate levels and satisfactory for predicting magnesium.Results of both developed networks were compared with the statistical model and found that ANN predictions are better than the conventional methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP Lambert Academic Publishing, 2017

      3330041625 / 9783330041622

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the Gaza Strip the maximum amount of the drinking water is produced through small private desalination plants. The present book is concerned with using artificial neural network (ANN) technique to forecast and predict the next week concentrations of total dissolved solids (TDS), chloride, nitrate and magnesium of the product water quality in the reverse osmosis desalination plants in the Gaza Strip. Multilayer perceptron (MLP) and radial basis function (RBF) neural networks were trained and developed with reference to product water parameters including: water temperature, pressure, pH and conductivity to predict TDS, chloride and nitrate next week values. MLP and RBF neural networks were trained and developed with reference to three water quality parameters including pressure, chloride and conductivity to predict magnesium concentrations. The prediction results showed that both types of neural networks are good for predicting TDS, chloride and nitrate levels and satisfactory for predicting magnesium.Results of both developed networks were compared with the statistical model and found that ANN predictions are better than the conventional methods.