Muhittin aslan (9 risultati)

Condizione: New. pp. 140.

Taschenbuch. Condizione: Neu. Neural Network and Fuzzy Logic Implementation on Lake Ecosystems | Lake Eymir Case - Turkey | Muhittin Aslan | Taschenbuch | 140 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846537084 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Modeling is a helpful tool that might be used to predict the Dissolved Oxygen (DO) level of a lake. Most ecological systems are complex and unstable. In case black box models might be essential instead of deterministic ones. DO in Eymir Lake was modeled by using both Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS). Phosphate, Orthophospate, pH, Chlorophyll-a, Temperature, Alkalinity, Nitrate,Total Kjeldahl Nitrogen, Wind, Precipitation, Air Temperature were the input parameters of ANN and ANFIS. The aims of these modeling studies were: developing models with ANN to predict DO level in Lake Eymir with high fidelity to actual DO data, to compare the success of ANN and ANFIS on DO modeling, to determine the degree of dependence of different parameters on DO. Matlab R 2007b software was used. The results indicated that ANN has high prediction capacity of DO and ANFIS has low with respect to ANN. Failure of ANFIS was due to low functionality of Matlab ANFIS. For ANN Modeling effect of meteorological data on DO data on surface of the lake was successfully described and summer month super saturation DO concentrations were successfully predicted. 140 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Modeling is a helpful tool that might be used to predict the Dissolved Oxygen (DO) level of a lake. Most ecological systems are complex and unstable. In case black box models might be essential instead of deterministic ones. DO in Eymir Lake was modeled by using both Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS). Phosphate, Orthophospate, pH, Chlorophyll-a, Temperature, Alkalinity, Nitrate,Total Kjeldahl Nitrogen, Wind, Precipitation, Air Temperature were the input parameters of ANN and ANFIS. The aims of these modeling studies were: developing models with ANN to predict DO level in Lake Eymir with high fidelity to actual DO data, to compare the success of ANN and ANFIS on DO modeling, to determine the degree of dependence of different parameters on DO. Matlab R 2007b software was used. The results indicated that ANN has high prediction capacity of DO and ANFIS has low with respect to ANN. Failure of ANFIS was due to low functionality of Matlab ANFIS. For ANN Modeling effect of meteorological data on DO data on surface of the lake was successfully described and summer month super saturation DO concentrations were successfully predicted.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Aslan MuhittinMuhittin ASLAN has received his Master of Science Degree o Environmental Engineering in 2008 from METU. Currently he is working for Ministry of Environment and Urbanisation of Turkey. Also he has doctorate studies regar.…

Condizione: New. Print on Demand pp. 140 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 140.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Modeling is a helpful tool that might be used to predict the Dissolved Oxygen (DO) level of a lake. Most ecological systems are complex and unstable. In case black box models might be essential instead of deterministic ones. DO in Eymir Lake was modeled by using both Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS). Phosphate, Orthophospate, pH, Chlorophyll-a, Temperature, Alkalinity, Nitrate,Total Kjeldahl Nitrogen, Wind, Precipitation, Air Temperature were the input parameters of ANN and ANFIS. The aims of these modeling studies were: developing models with ANN to predict DO level in Lake Eymir with high fidelity to actual DO data, to compare the success of ANN and ANFIS on DO modeling, to determine the degree of dependence of different parameters on DO. 'Matlab R 2007b' software was used. The results indicated that ANN has high prediction capacity of DO and ANFIS has low with respect to ANN. Failure of ANFIS was due to low functionality of Matlab ANFIS. For ANN Modeling effect of meteorological data on DO data on surface of the lake was successfully described and summer month super saturation DO concentrations were successfully predicted.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.…