A Recurrent Neural Network Model for solving BCC Model in Data Envelopment Analysis
عنوان مقاله: A Recurrent Neural Network Model for solving BCC Model in Data Envelopment Analysis
شناسه ملی مقاله: DEA09_065
منتشر شده در نهمین کنفرانس ملی تحلیل پوششی داده ها در سال 1396
شناسه ملی مقاله: DEA09_065
منتشر شده در نهمین کنفرانس ملی تحلیل پوششی داده ها در سال 1396
مشخصات نویسندگان مقاله:
A Ghomashi - Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
M Abbasi - Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
S Shahghobadi - Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
خلاصه مقاله:
A Ghomashi - Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
M Abbasi - Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
S Shahghobadi - Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
In this paper we present a recurrent neural network model for solving BCC Modelin Data Envelopment Analysis(DEA).The proposed neural network model is derived from an unconstrained minimization problem.In theoretical aspect, it is shown that the proposed neural network is stable in the sense oflyapunov and globally convergent. The proposed model has a single-layer structure.Simulation shows that the proposed model is effective to identify efficient DMUs in DEA.
کلمات کلیدی: Recurrent neural network, Gradient method, Data envelopment analysis, Efficient DMU, Stability, Global convergence
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/678410/