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Synopsis
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.
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Authors 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 works/ reviewing research papers in international journals and editorial board member of many international journals.
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Application of Artificial Neural Networks for Predicting Water Quality
Published by
LAP Lambert Academic Publishing Feb 2017, 2017
ISBN 10: 3330041625
ISBN 13: 9783330041622
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: 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. Seller Inventory # 9783330041622
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Application of Artificial Neural Networks for Predicting Water Quality
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330041625
ISBN 13: 9783330041622
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Seller: moluna, Greven, Germany
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Condition: 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. Seller Inventory # 158123022
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Application of Artificial Neural Networks for Predicting Water Quality
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330041625
ISBN 13: 9783330041622
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Paperback
Seller: Revaluation Books, Exeter, United Kingdom
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Paperback. Condition: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock. Seller Inventory # 3330041625
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Application of Artificial Neural Networks for Predicting Water Quality
Published by
LAP Lambert Academic Publishing Feb 2017, 2017
ISBN 10: 3330041625
ISBN 13: 9783330041622
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Seller Inventory # 9783330041622
Quantity: 2 available
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Application of Artificial Neural Networks for Predicting Water Quality
Published by
LAP Lambert Academic Publishing, 2017
ISBN 10: 3330041625
ISBN 13: 9783330041622
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9783330041622
Quantity: 1 available