Name
Abstract | ||
|---|---|---|
Microflora population of poultry was affected by various factors. Many methods and techniques were developed to study microflora population. But, most of them confronted some problems. Moreover, being costly, laborious, and time-consuming made it impossible to measure microflora population several times. In this study, we tried to estimate intestinal microflora population using artificial neural network (ANN). Lactic acid bacteria were used as model of microflora population. Time and lactic acid bacteria were used as input and output variables, respectively. The best model of ANN was determined based on coefficient of determination, root mean square error, and mean absolute error criteria. The results of current study have shown that ANN is appropriate, cheap, and reliable tools to estimate intestinal microflora population (lactic acid bacteria) of broiler at different ages. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s00521-011-0553-2 | Neural Computing and Applications |
Keywords | DocType | Volume |
best model,current study,different age,lactic acid bacterium,output variable,absolute error criterion,intestinal microflora population,intestinal broiler microflora estimation,square error,Microflora population,artificial neural network,modeling microflora population broiler | Journal | 21 |
Issue | ISSN | Citations |
5 | 1433-3058 | 1 |
PageRank | References | Authors |
0.63 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamid Reza Hemati Matin | 1 | 1 | 0.96 |
| Ali Asghar Saki | 2 | 1 | 0.96 |
| Hasan Aliarabi | 3 | 1 | 0.63 |
| Mojtaba Shadmani | 4 | 1 | 0.63 |
| Hamid Zare Abyane | 5 | 1 | 0.63 |