‎By p-power (or partial p-power) transformation‎, ‎the Lagrangian function in nonconvex optimization problem becomes locally convex‎. ‎In this paper‎, ‎we present a neural network based on an NCP function for solving the nonconvex optimization problem‎. An important feature of this neural network is the one-to-one correspondence between its equilibria and KKT points of the nonconvex optimizatio...

In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as  amount  of  flow  intensity  ratio,  temperature,  residence  time,  and  pH  are  used  as  input  variables  of  the network,  whereas  the  extraction  yield  is  considere...

Geological facies interpretation is essential for reservoir studying. The method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. Use of neural networks as classifiers is increasing in different sciences like seismic. They are computer efficient and ideal for patterns identification. They can simply learn new algori...

Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...

In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...

In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in 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 of lyapunov and globally convergent. The proposed model has a single-laye...

Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

Tailor-made blanks are sheet metal assemblies with different thicknesses and/or materials and/or surface coatings. A monolithic sheet can be machined to make the required thickness variations that is referred as tailor machined blanks. Due to the thickness variation in tailor machined blanks, laser bending of these blanks is more complicated than monolithic plates. In this article, laser formin...