1. Adamchuk, V. I., A. V. Skotnikov, J. D. Speichinger, and M. F. Kocher. 2004. Development of an instrumented deep-tillage implement for sensing of soil mechanical resistance. Trans. ASAE. 47: 1913-191.
2. Anami, B. S., J. D. Pujari, and R. Yakkhundimath. 2011. Identification and classification of normal and affected agriculture/horticulture produce based on combined color and texture feature extraction. International Journal of Computer Applications in Engineering Sciences 1: 356-360.
3. Arjona, R., P. Ollero, and F. Vidal. 2005. Automation of an olive waste industrial rotary dryer. Journal of Food Engineering 68: 239-242.
4. Azadeh, A., S. F. Ghaderi, and S. Sohrabkhani. 2006. Forecasting electrical consumption by integration of Neural Network, time series and ANOVA.
5. Ishikawa, S., and V. Gulick. 2013. An automated mineral classifier using Raman spectra. Computers and Geosciences 54: 259-268.
6. Jacovides, C. P. 1997. Reply to comment on Statistical procedures for the evaluation of evapotranspiration models. Agricultural Water Management 3: 95-97.
7. Kaul, M., R. L. Hill, and C. Walthall. 2005. Artificial neural networks for corn and soybean yield prediction. Agriculture system 85: 1-18.
8. Keshavarz, J. 2014. Design, fabrication and evaluation of the electronic control system of temperature and humidity, in the industrial poultry farm. M. Sc. Thesis, Faculty of Agricultural, Bahonar University. (In Farsi).
9. Moallem, P., and A. Monajemi. 2007. A heuristic criterion for goodness of multi layer perceptron as a classifier. First Data Mining Conference. Amir Kabir University, Tehran, Iran. (In Farsi).
10. Rashed Mohassel, M. H., H. Najafi, and M. D. Akbarzadeh. 2001. Weed Biology and Control. Ferdowsi University Press, 404p. (In Farsi).
11. Rizzoni, G. 2000. Principels and Applications of Electrical Engineering, 3td ed., McGraw-Hill, USA.
12. Sigari, M. H., H. Sigari, and N. Mozayani. 2012. Estimated time of drying food using computer vision and artificial neural network. Fifth National Conference on Agricultural Machinery Engineering and Mechanisation. Ferdowsi University, Mashhad, Iran. (In Farsi).
13. Simmons, J. D., and B. D. Loit. 1993. Automatic Fan Control, Agricultural Research Service, South Central Poultry Research Laboratory, Mississipi Stat. pp. 323-2230.
14. Storey, N., 1998. Electronics: A system approach, Prentice Hall, Harlow.
15. Torrecilla, J. S., L. Otero, and P. D. Sanz. 2004. A neural network approach for thermal/pressure food processing. Food Engineering 62: 89-95.
16. Vakil-Baghmisheh, M. T. 2002. Farsi Character Recognition Using Artificial Neural Networks. PhD Thesis, Faculty of Electrical Engineering, University of Ljubljana.
17. Visen, N. S., D. S. Jayas, J. Paliwal, and N. D. G. White. 2004. Comparison of two neural network architectures for classification of singulated cereal grains. Journal of Canadian Biosystem Engineering 46: 7-14.
18. Zhang, Q., S. Y. Yang, G. S. Mittal, and S. Yi. 2002. Prediction of performance indices and optimal parameters of rough rice drying using neural network. Biosystems Engineering 83 (3): 281-290.
19. Zhang, Y. F., and J. Y. H. Fun. 1998. A neural network approach for early cost estimation of packaging products. Computers & Industrial Engineering 34: 433-50.
ارسال نظر در مورد این مقاله