International Scientific and Vocational Studies Journal

International Scientific and Vocational Studies Journal

The Sunshine Duration Error Rates were calculated with Gradient-Descent Algorithm and Genetic Algorithm for Use of Solar Energy

Yazarlar: Yalçın KAPLAN

Cilt 1 , Sayı 1 , 2017 , Sayfalar 42 - 50

Konular:Mühendislik, Elektrik ve Elektronik

Anahtar Kelimeler:Neural network,Energy,Sunshine

Özet: In this study, which is a source of renewable energy required to take advantage of solar energy to the maximum duration of sunshine was estimated. In the study, values were used of the city of Amasya. Artificial neural networks (ANN) backpropagation gradient-descent(GD) learn algorithm and genetic algorithm(GA) were used. Three hidden layer network model was designed with two inputs for ANN and GA. Between 2000 and 2010 values were used as input data monthly sunshine duration and humidity values. Output data was obtained monthly sunshine duration of 2010. The values obtained were compared with the actual values and the root mean square error (RMSE) was calculated. Result of the study, GA was used to calculate the values that are needed for solar energy.

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@article{2017, title={The Sunshine Duration Error Rates were calculated with Gradient-Descent Algorithm and Genetic Algorithm for Use of Solar Energy}, volume={1}, number={1}, publisher={International Scientific and Vocational Studies Journal}, author={Yalçın KAPLAN}, year={2017}, pages={42–50} }
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Yalçın KAPLAN. (2017). The Sunshine Duration Error Rates were calculated with Gradient-Descent Algorithm and Genetic Algorithm for Use of Solar Energy (Vol. 1, pp. 42–50). Vol. 1, pp. 42–50. International Scientific and Vocational Studies Journal.
MLA
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Yalçın KAPLAN. The Sunshine Duration Error Rates Were Calculated with Gradient-Descent Algorithm and Genetic Algorithm for Use of Solar Energy. no. 1, International Scientific and Vocational Studies Journal, 2017, pp. 42–50.
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