Title of article
A Recurrent Neural Network Model for Solving CCR Model in Data Envelopment Analysis
Author/Authors
Abbasi, Masomeh Department of Mathematics - Kermanshah Branch - Islamic Azad University , Ghomashi, Abbas Department of Mathematics - Kermanshah Branch - Islamic Azad University
Pages
7
From page
1
To page
7
Abstract
In this paper, we present a recurrent neural network model for solving
CCR Model in Data Envelopment Analysis (DEA). The proposed
neural network model is derived from an unconstrained minimization
problem. In the theoretical aspect, it is shown that the proposed neural
network is stable in the sense of Lyapunov and globally convergent
to the optimal solution of CCR model. The proposed model has a single-
layer structure. A numerical example shows that the proposed
model is effective to solve CCR model in DEA.
Keywords
Recurrent neural network , Gradient method , Data envelopment analysis , CCR , Stability Global convergence
Journal title
Astroparticle Physics
Serial Year
2019
Record number
2436297
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