Research Article

Application of Artificial Neural Network for Wheat Type Classification: A Novel Artificial Intelligence Training Software

Volume: 21 Number: 3 October 23, 2018
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Application of Artificial Neural Network for Wheat Type Classification: A Novel Artificial Intelligence Training Software

Abstract

In this study, a training software with a visual interface was developed by using C# programming language in .NET platform for the purpose of using it in artificial neural networks’ training. The created artificial neural network classification software was applied on wheat type classification case study and successful results were achieved. Additionally, the importance of artificial neural networks was mentioned in the study. Backpropagation algorithm was utilized in wheat type classification case and in the developed software in order to eliminate the difficulty and complexity of the use of current software in an artificial neural network training process. Additionally, the developed software was designed in flexible and convenient structure as to be used in the applications which could be solved with artificial neural networks and other all kinds of studies.

Keywords

References

  1. CireşAn, D., Meier, U., Masci, J., & Schmidhuber, J. (2012). Multi-column deep neural network for traffic sign classification. Neural Networks, 32, 333-338.
  2. Elmas, Ç. (2003). Yapay Sinir Ağları. Seçkin Yayıncılık, Ankara, 27-37.
  3. Elmas, Ç. (2007). Yapay zeka uygulamaları. Seçkin Yayıncılık, Ankara, 379-401.
  4. Fausett, L., & Fausett, L. (1994). Fundamentals of neural networks: architectures, algorithms, and applications (No. 006.3). Prentice-Hall.
  5. Hagan, M. T., Demuth, H. B., & Beale, M. H. (1996). Neural network design, PWS Pub. Co., Boston, 3632. Haykin, S. (1994). Neural networks: a comprehensive foundation. Prentice Hall PTR.
  6. Kaastra, I., & Boyd, M. (1996). Designing a neural network for forecasting financial and economic time series. Neurocomputing, 10(3), 215-236.
  7. Kılıç, H. B. (1998). Yapay Sinir Ağları İle Karakter Algılama. Yüksek Lisans Tezi, Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Ankara.
  8. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.

Details

Primary Language

English

Subjects

Computer Software , Engineering

Journal Section

Research Article

Authors

Müslüm Öztürk
KİLİS 7 ARALIK ÜNİVERSİTESİ
Türkiye

Turan Paksoy
SELÇUK ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ
Türkiye

Publication Date

October 23, 2018

Submission Date

August 4, 2017

Acceptance Date

September 26, 2018

Published in Issue

Year 2018 Volume: 21 Number: 3

APA
Öztürk, M., & Paksoy, T. (2018). Application of Artificial Neural Network for Wheat Type Classification: A Novel Artificial Intelligence Training Software. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 21(3), 246-257. https://doi.org/10.17780/ksujes.332770

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