Modeling of Short Term Load Forecasting for Khartuom State Using ANN
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Modeling of Short Term Load Forecasting for Khartuom State Using ANN
DE PB NWISBN: 9783659851124 bzw. 3659851124, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Modeling of Short Term Load Forecasting for Khartuom State Using ANN: Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%. Englisch, Taschenbuch.
Modeling of Short Term Load Forecasting for Khartuom State Using ANN: Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%. Englisch, Taschenbuch.
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Modeling of Short Term Load Forecasting for Khartuom State Using ANN
DE NWISBN: 9783659851124 bzw. 3659851124, in Deutsch, neu.
Lieferung aus: Deutschland, Lieferzeit: 7 Tage.
Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%.
Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%.
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Modeling of Short Term Load Forecasting for Khartuom State Using ANN
~EN NW ABISBN: 9783659851124 bzw. 3659851124, vermutlich in Englisch, neu, Hörbuch.
Lieferung aus: Österreich, Lieferzeit: 5 Tage, zzgl. Versandkosten.
Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%.
Electric load forecasting is the process used to forecast future electric load, given historical load, weather information and current weather information. This work developed model for STLF using Artificial Neural Network (ANNs) approach. Artificial Neural Network (ANN) method is applied to forecast the short-term load for Khartoum State. A nonlinear load model for the load is proposed and several structures of ANN for short-term load forecasting are tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one hidden layer is tested with various combinations of neurons, and results are compared in terms of forecasting error. The model, when tested for seven random days, gives average percentage error of 3.11%.
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Modeling of Short Term Load Forecasting for Khartuom State Using ANN als von Ashraf Musa
DE HC NWISBN: 9783659851124 bzw. 3659851124, in Deutsch, gebundenes Buch, neu.
Lieferung aus: Deutschland, zzgl. Versandkosten.
Modeling of Short Term Load Forecasting for Khartuom State Using ANN ab 49.9 EURO, Modeling of Short Term Load Forecasting for Khartuom State Using ANN ab 49.9 EURO.
Modeling of Short Term Load Forecasting for Khartuom State Using ANN ab 49.9 EURO, Modeling of Short Term Load Forecasting for Khartuom State Using ANN ab 49.9 EURO.
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Modeling of Short Term Load Forecasting for Khartuom State Using ANN
~EN PB NWISBN: 3659851124 bzw. 9783659851124, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Modeling of Short Term Load Forecasting for Khartuom State Using ANN ab 49.9 € als Taschenbuch: . Aus dem Bereich: Bücher, Wissenschaft, Physik,.
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Modeling of Short Term Load Forecasting for Khartuom State Using ANN als von
DE HC NWISBN: 9783659851124 bzw. 3659851124, in Deutsch, LAP Lambert Academic Publishing, gebundenes Buch, neu.
Modeling of Short Term Load Forecasting for Khartuom State Using ANN: Ashraf Musa Modeling of Short Term Load Forecasting for Khartuom State Using ANN: Ashraf Musa.
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