, Volume 60, Issue 2, pp 153–160 | Cite as

Design of Neural Network Predictor for the Physical Properties of Almond Nuts

  • İkbal Eski
  • Bünyamin DemirEmail author
  • Feyza Gürbüz
  • Zeynel Abidin Kuş
  • Kadir Uğurtan Yilmaz
  • Mehmet Uzun
  • Sezai Ercişli
Original Article


In this study, an adaptive neuro fuzzy interface system (ANFIS) based predictor was designed to predict the physical properties of four almond types. Measurements of the dimensions, length, width and thickness were carried out for one hundred randomly selected samples of each type. With using these three major perpendicular dimensions, some physical parameters such as projected area, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, shape index and aspect ratio were estimated. In in a various Artificial Neural Network (ANN) structures, ANFIS structure which has given the best results was selected. The parameters analytically estimated and those predicted were given in the form of figures. The root mean-squared error (RMSE) was found to be 0.0001 which is quite low. ANFIS approach has given a superior outcome in the prediction of the Physical Properties of Almond Nuts.


Neural Network Almond nut Prediction Physical properties 

Design des neuronalen Netzes als Prädiktor für die physikalischen Eigenschaften von Mandeln


Neuronales Netz Mandel Prognose Physikalische Eigenschaften 


Conflict of interest

B. Demir, İ. Eski, F. Gürbüz, Z. Abidin Kuş, K. Uğurtan Yilmaz, M. Uzun and S. Ercişli declare that they have no competing interests.


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Copyright information

© Springer-Verlag GmbH Deutschland 2017

Authors and Affiliations

  • İkbal Eski
    • 1
  • Bünyamin Demir
    • 2
    Email author
  • Feyza Gürbüz
    • 3
  • Zeynel Abidin Kuş
    • 4
  • Kadir Uğurtan Yilmaz
    • 5
  • Mehmet Uzun
    • 6
  • Sezai Ercişli
    • 7
  1. 1.Department of Mechatronics Engineering, Faculty of EngineeringUniversity of ErciyesKayseriTurkey
  2. 2.Department of Mechanical and Metal Technologies, Vocational School of Technical SciencesUniversity of MersinMersinTurkey
  3. 3.Department of Industrial Engineering, Faculty of EngineeringUniversity of ErciyesKayseriTurkey
  4. 4.Department of Biosystems Engineering, Faculty of AgricultureUniversity of ErciyesKayseriTurkey
  5. 5.Department of Horticulture, Faculty of AgricultureUniversity of ErciyesKayseriTurkey
  6. 6.Pistachio Research InstituteGaziantepTurkey
  7. 7.Department of Horticulture, Faculty of AgricultureUniversity of AtatürkErzurumTurkey

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