Perusing the influence of desired value on Back Propagation Neural Network using Data Envelopment Analysis Models in Supplier Selection Evaluation
Perusing the influence of desired value on Back Propagation Neural Network using Data Envelopment Analysis Models in Supplier Selection Evaluation
sahar ghafari khenari1 fateme ghafari khenari2
1) Iran Islamic Azad University, Central Tehran Branch Email:
2) Iran Islamic Azad University, Sciences & Research Branch Email:
Publication :
International Conference On Research Science And Technology(restconf.com)
Abstract :
Based on the complexity and diversity of the features of the supplier efficiency and performance evaluation toady, neural networks can be used. There are several papers that use supervised neural networks to evaluate the efficiency of the decision making units, by a set of desired value needed.
This paper aims to peruse the quality of the desired value on the neutral network training and predicting. Hence here we use SBM, SBM-Output oriented and Russell models efficiency scores to introduce new sets of desired value in supplier selection evaluation process by neural network. Then compare the gained results together to find the best set of desired value for network for supplier selection evaluation.
Keywords :
Data Envelopment Analysis (DEA)
Back Propagation Neural Network (BPNN)
Desire Value