this paper describes an advantageous method for using the capacitor banks in the distribution network, optimally. the aim is to determine the count, location and capacitor values in order to minimize the annual cost resulting from energy losses and capacitor bank’s installation cost. besides, in the case of having nonlinear loads in the network, by installing capacitors in appropriate locations...

estimating the final price of products is of great importance. for manufacturing companies proposing a final price is only possible after the design process over. these companies propose an approximate initial price of the required products to the customers for which some of time and money is required. here using the existing data of already designed transformers and utilizing the bayesian anal...

glaucoma, a group of multifactor ocular diseases, is the second leading cause of blindness worldwide. primary open angle (poa) is the most common type of glaucoma, characterized by progressive optic nerve degeneration. numerous genes and proteins have been revealed to be associated with poag, but the pathologic mechanisms of the disease are still poorly understood. proteomics, the collective st...

Reducing or eliminating statistical redundancy between the components of high-dimensional vector data enables a lower-dimensional representation without significant loss of information. Recognizing the limitations of principal component analysis (PCA), researchers in the statistics and neural network communities have developed nonlinear extensions of PCA. This article develops a local linear ap...

Convex optimization techniques are widely used in the design and analysis of communication systems and signal processing algorithms. In this paper a novel recurrent neural network is presented for solving nonlinear strongly convex equality constrained optimization problems. The proposed neural network is based on recursive quadratic programming for nonlinear optimization, in conjunction with ho...

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a modelbased approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component an...