The Fate of The Poultry Industry Forecasting in Kurdistan Region by Using Neural Networks تنبؤات صناعة الدواجن في منطقة کردستان من خلال استخدام الشبکات العصبية
babaca, Z., Rashid, R., Sofee, Y. (2020). The Fate of The Poultry Industry Forecasting in Kurdistan Region by Using Neural Networks تنبؤات صناعة الدواجن في منطقة کردستان من خلال استخدام الشبکات العصبية. EKB Journal Management System, 11(10), 421-424. doi: 10.21608/jappmu.2020.123637
zahir abdullateef babaca; Rakan S. Rashid; Younis Y. Sofee. "The Fate of The Poultry Industry Forecasting in Kurdistan Region by Using Neural Networks تنبؤات صناعة الدواجن في منطقة کردستان من خلال استخدام الشبکات العصبية". EKB Journal Management System, 11, 10, 2020, 421-424. doi: 10.21608/jappmu.2020.123637
babaca, Z., Rashid, R., Sofee, Y. (2020). 'The Fate of The Poultry Industry Forecasting in Kurdistan Region by Using Neural Networks تنبؤات صناعة الدواجن في منطقة کردستان من خلال استخدام الشبکات العصبية', EKB Journal Management System, 11(10), pp. 421-424. doi: 10.21608/jappmu.2020.123637
babaca, Z., Rashid, R., Sofee, Y. The Fate of The Poultry Industry Forecasting in Kurdistan Region by Using Neural Networks تنبؤات صناعة الدواجن في منطقة کردستان من خلال استخدام الشبکات العصبية. EKB Journal Management System, 2020; 11(10): 421-424. doi: 10.21608/jappmu.2020.123637

The Fate of The Poultry Industry Forecasting in Kurdistan Region by Using Neural Networks تنبؤات صناعة الدواجن في منطقة کردستان من خلال استخدام الشبکات العصبية

Journal of Animal and Poultry Production
Article 7, Volume 11, Issue 10, October 2020, Page 421-424  XML PDF (1.12 MB)
Document Type: Original Article
DOI: 10.21608/jappmu.2020.123637
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Authors
zahir abdullateef babaca email 1; Rakan S. Rashid2; Younis Y. Sofee3
1Nursing department, Bardarash technical institute, Duhok polytechnic university, Duhok, Iraq
2Department of IT, Bardarash Technical Institution, Dohuk Rakan.rashid@ dpu.edu.krd
3Shaqlawa Veterinary Hospital, Erbil techmag2011@yahoo.com
Abstract
The most recent studies demonstrate the predictive power of neural-networks. Used neural-networks were success to predict of economic results trends, and the neural-networks have an advantage, whereas its can the nonlinear functions approximate. In doing so, it can provide the alternative analysis regression of the biology of modeling growth. Some Few searches were conducted by neural-networks on the animal growth model artificially. The present study was conducted to compare, the parameters of various associated input performance. For example, the chickens price/kg in poultry farm, the price/tons of poultry feed, the quantity import of white meat, and the numbers of chickens slaughtered, which is expected to be of help in future for our study. We applied series of data/monthly for rates exchange in between 2009 to 2014. Aims of recent study in the first place; to develop ANN- based models to study the Fate of the Poultry Industry Forecasting in Kurdistan Region. Secondly, through previous data we can recommend that, neural-networks method, more suitable in chicken industries, than the simple analysis regression, if accurate data are collected and processed in such forms.
Keywords
Neural Networks; Poultry Industry; Forecasting
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