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Singh, T. P.
- Comparative Study of Feed-Forward Neuro-Computing with Multiple Linear Regression Model for Milk Yield Prediction in Dairy Cattle
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PDF Views:71
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1 Symbiosis Institute of Geoinformatics, Symbiosis International University, Pune 411 016, IN
1 Symbiosis Institute of Geoinformatics, Symbiosis International University, Pune 411 016, IN
Source
Current Science, Vol 108, No 12 (2015), Pagination: 2257-2261Abstract
The main objective of this work is to compare the accuracy of artificial neural networks (ANNs) and multiple linear regression (MLR) model for prediction of first lactation 305-day milk yield (FL305DMY) using monthly test-day milk yield records of 443 Frieswal cows. We have compared four versions of feed forward algorithm with conventional statistical model. The performancre of ANN is found to be better than the MLR model for milk yield prediction. The Bayesian regularization neural network model was able to predict milk yield with 85.07% accuracy as early as 126th day of lactation. It has been found that R2 value of the models increases with increase in the number of test-day milk yield records.Keywords
Artificial Neural Network, Dairy Cattle, Milk Yielded, Multiple Linear Regression.Full Text
- Development of Lifetime Milk Yield Equation Using Artificial Neural Network in Holstein Friesian Cross Breddairy Cattle and Comparison with Multiple Linear Regression Model
Abstract Views :276 |
PDF Views:68
Authors
Affiliations
1 Symbiosis Institute of Geo-Informatics, Symbiosis International University, Pune 411 016, IN
1 Symbiosis Institute of Geo-Informatics, Symbiosis International University, Pune 411 016, IN
Source
Current Science, Vol 113, No 05 (2017), Pagination: 951-955Abstract
The scope of this study was to develop lifetime milk yield (LTMY) prediction equation using different economical traits. The traits used were first lactation length, first peak yield, first lactation total milk yield,and total of three lactation milk yield of 1210 Holstein Friesian crossbred dairy cattle in India. Four variants of feed-forward back propagation algorithms were compared with the multiple linear regression model.The performance of Bayesian regularization (BR) algorithm was found to be better than the other algorithms for LTMY prediction. The BR neural network model was able to predict milk yield with 71.18% R2.Keywords
Artificial Neural Network, Cows, Lifetime Milk Yield, Multiple Linear Regression.Full Text
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