Click for new scientific resources and news about Corona[COVID-19]

Paper Information

Journal:   IRANIAN JOURNAL OF APPLIED ANIMAL SCIENCE   JUN 2014 , Volume 4 , Number 2; Page(s) 411 To 416.
 
Paper: 

APPLICATION OF LINEAR REGRESSION AND ARTIFICIAL NEURAL NETWORK FOR BROILER CHICKEN GROWTH PERFORMANCE PREDICTION

 
 
Author(s):  GHAZANFARI S.*
 
* DEPARTMENT OF ANIMAL SCIENCE, COLLEGE OF ABOURAIHAN, UNIVERSITY OF TEHRAN, TEHRAN, IRAN
 
Abstract: 

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kcal/kg) and crude protein (g/kg) and outputs of feed intake, weight gain and feed conversion ratio variables. High R2 and T values for the ANN model in comparison to linear regression revealed that the artificial neural network (ANN) is an efficient method for growth performance prediction in the starter period for broiler chickens. This study also focused on expanding the experiment with more levels of inputs to predict outputs the using best ANN model.

 
Keyword(s): ARTIFICIAL NEURAL NETWORK, BACK PROPAGATION ALGORITHM, BROILER CHICKEN, GROWTH PERFORMANCE, LINEAR REGRESSION
 
 
References: 
 
Click to Cite.
APA: Copy

GHAZANFARI, S. (2014). APPLICATION OF LINEAR REGRESSION AND ARTIFICIAL NEURAL NETWORK FOR BROILER CHICKEN GROWTH PERFORMANCE PREDICTION. IRANIAN JOURNAL OF APPLIED ANIMAL SCIENCE, 4(2), 411-416. https://www.sid.ir/en/journal/ViewPaper.aspx?id=407474



Vancouver: Copy

GHAZANFARI S.. APPLICATION OF LINEAR REGRESSION AND ARTIFICIAL NEURAL NETWORK FOR BROILER CHICKEN GROWTH PERFORMANCE PREDICTION. IRANIAN JOURNAL OF APPLIED ANIMAL SCIENCE. 2014 [cited 2021May12];4(2):411-416. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=407474



IEEE: Copy

GHAZANFARI, S., 2014. APPLICATION OF LINEAR REGRESSION AND ARTIFICIAL NEURAL NETWORK FOR BROILER CHICKEN GROWTH PERFORMANCE PREDICTION. IRANIAN JOURNAL OF APPLIED ANIMAL SCIENCE, [online] 4(2), pp.411-416. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=407474.



 
  pdf-File
Yearly Visit 70
 
Latest on Blog
Enter SID Blog