Yield prediction of wheat in south-east region of Turkey by using artificial neural networks

Yuksel Cakir*, Murvet Kirci, Ece Olcay Gunes

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

17 Atıf (Scopus)

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 dilİngilizce
Ana bilgisayar yayını başlığı2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781479941575
DOI'lar
Yayın durumuYayınlandı - 25 Eyl 2014
Harici olarak yayınlandıEvet
Etkinlik2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 - Beijing, China
Süre: 11 Ağu 201414 Ağu 2014

Yayın serisi

Adı2014 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
Ülke/BölgeChina
ŞehirBeijing
Periyot11/08/1414/08/14

Bibliyografik not

Publisher Copyright:
© 2014 IEEE.

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