@article{MAKHILLRJPS20125327866,
    title = {Improve Poultry Farm Efficiency in Iran: Using Combination Neural Networks, Decision Trees and Data Envelopment Analysis (DEA)},
    journal = {Research Journal of Poultry Sciences},
    volume = {5},
    number = {3},
    pages = {39-49},
    year = {2012},
    issn = {1993-5285},
    doi = {rjpscience.2012.39.49},
    url = {https://makhillpublications.co/view-article.php?issn=1993-5285&doi=rjpscience.2012.39.49},
    author = {Iman and},
    keywords = {Data envelopment analysis,decision tree,artificial neural network,poultry meat farming,efficiency},
    abstract = {Since, poultry meat farming sub-sector has high potential 
  for enhancing the agriculture industry in comparison to other sub-sectors. Therefore, 
  evaluation of Decision Making Units (DMUs) of poultry in provinces and hence 
  improving them is important task to the whole agriculture. Besides, there exist 
  several proposed approaches to resolve this problem. However, a different methodology 
  is proposed due to its powerful discriminatory performance, in this research. 
  For this purpose, combination of Data Envelop Analysis (DEA) and requisite data 
  mining techniques same as Artificial Neural Network (ANN) and Decision Tree 
  (DT) are employed in order to enhance the power of predicting the DMUs evaluation 
  performance because of their well-known efficiency and thereby to present precise 
  decision rules for improving their efficiency. To illustrate the proposed model, 
  all poultry companies in Iran were taken into account. However, in this case 
  there is a small dataset and because the large dataset is necessary to collect 
  data as well as to apply data mining methodology, so, researchers employed k-fold 
  cross validation method to validate the model. Consequently, applied model is 
  supposed to predict efficiency of DMUs and thereby to present decision rules 
  in order to improve the efficiency precisely and accurately according to used 
  optimizing techniques.}
    }