Özet
In Turkey, similarly to other grain producing countries, the prediction of wheat yield is an important problem. The objective in this study is to build an artificial neural network model that could effectively predict wheat yield by using meteorological data such as temperature and rainfall records. Multi-Layer Perceptron neural network model was chosen and the performance of the built network was tested for different input and neurons number. For defining the model parameters back propagation training technique was used. During the training of the network, various learning rates were chosen and the optimal values for these parameters were defined. For the final assessment of the obtained results a multiple parameter linear regression model was developed and tested with the same data set used for the built artificial neural network.
Orijinal dil | İngilizce |
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Ana bilgisayar yayını başlığı | 2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Elektronik) | 9781479941575 |
DOI'lar | |
Yayın durumu | Yayınlandı - 25 Eyl 2014 |
Harici olarak yayınlandı | Evet |
Etkinlik | 2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 - Beijing, China Süre: 11 Ağu 2014 → 14 Ağu 2014 |
Yayın serisi
Adı | 2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 |
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???event.eventtypes.event.conference??? | 2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 |
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Ülke/Bölge | China |
Şehir | Beijing |
Periyot | 11/08/14 → 14/08/14 |
Bibliyografik not
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