Items related to APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE:...
- PublisherLAP LAMBERT Academic Publishing
- Publication date2023
- ISBN 10 6206753468
- ISBN 13 9786206753469
- BindingPaperback
- LanguageEnglish
- Number of pages84
Search results for APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE:...
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APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206753468
ISBN 13: 9786206753469
New
Softcover
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. Seller Inventory # 26400979581
Quantity: 4 available
Stock Image
APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206753468
ISBN 13: 9786206753469
New
Softcover
Seller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Print on Demand. Seller Inventory # 395430306
Quantity: 4 available
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APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206753468
ISBN 13: 9786206753469
New
Softcover
Seller: Biblios, Frankfurt am main, HESSE, Germany
Seller rating 5 out of 5 stars
Condition: New. PRINT ON DEMAND. Seller Inventory # 18400979575
Quantity: 4 available
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APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE
Published by
LAP LAMBERT Academic Publishing Jul 2023, 2023
ISBN 10: 6206753468
ISBN 13: 9786206753469
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Rainfall is very important parameter in hydrological model. Many techniques and models have been developed for rainfall forecasting. This study present a method of rainfall forecasting by developing an ANN- based model using major weather variables such as dry bulb temperature, wet bulb temperature, relative humidity, pan evaporation, vapour pressure as inputs while the rainfall as the target output. As part of the ANN model development procedures, the data sets of 11956 data in the study area was partitioned into two parts with 70% of the entire data sets used as the training data while the remaining 30% used as the testing and the validation data. The proposed model has been able to predict values with suitable results. For the evaluation of the results and the ability of the developed prognostic models, appropriate statistical indexes such as the coefficient of determination (R2), the Root mean square error (RMSE), Mean square error (MSE), Nash-Sutcliffe efficiency (EF), Akaike information criteria (AIC), Bayesian information criteria (BIC) were used. The findings from this analysis showed that the ANN model 5-5-3-1 provides satisfactory results based on statistical indexes. 84 pp. Englisch. Seller Inventory # 9786206753469
Quantity: 2 available
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APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE : Rainfall Forecasting
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206753468
ISBN 13: 9786206753469
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 - Rainfall is very important parameter in hydrological model. Many techniques and models have been developed for rainfall forecasting. This study present a method of rainfall forecasting by developing an ANN- based model using major weather variables such as dry bulb temperature, wet bulb temperature, relative humidity, pan evaporation, vapour pressure as inputs while the rainfall as the target output. As part of the ANN model development procedures, the data sets of 11956 data in the study area was partitioned into two parts with 70% of the entire data sets used as the training data while the remaining 30% used as the testing and the validation data. The proposed model has been able to predict values with suitable results. For the evaluation of the results and the ability of the developed prognostic models, appropriate statistical indexes such as the coefficient of determination (R2), the Root mean square error (RMSE), Mean square error (MSE), Nash-Sutcliffe efficiency (EF), Akaike information criteria (AIC), Bayesian information criteria (BIC) were used. The findings from this analysis showed that the ANN model 5-5-3-1 provides satisfactory results based on statistical indexes. Seller Inventory # 9786206753469
Quantity: 1 available
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APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUE
Published by
LAP Lambert Academic Publishing, 2023
ISBN 10: 6206753468
ISBN 13: 9786206753469
New
Softcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 1046991019
Quantity: Over 20 available