The performance of Neural Networks (NN) depends on network structure, activation function and suitable weight values. For finding optimal weight values, freshly, computer scientists show the interest in the study of social insect’s behavior learning algorithms. Chief among these are, Ant Colony Optimzation (ACO), Artificial Bee Colony (ABC) algorithm, Hybrid Ant Bee Colony (HABC) algorithm and ...

Abstract Traditional atmospheric models are based on the analysis and fitting of various factors influencing space atmosphere density. Neural network do not specifically analyze polynomials each factor in model, but use large data sets for construction. Two traditional model algorithms analyzed, main affecting identified, an neural networks containing is proposed. According to simulation error,...

The inverse problem in acousto-electric tomography concerns the reconstruction of electric conductivity a body from knowledge power density function interior body. This results currents prescribed at boundary electrodes, and it can be obtained through electro-static measurements together with auxiliary acoustic probing. Previous works on used continuum model for electrostatic conditions; howeve...

Abstract This paper presents a parallel approach to the Levenberg-Marquardt algorithm (LM). The use of train neural networks is associated with significant computational complexity, and thus computation time. As result, when network has big number weights, becomes practically ineffective. article new computations in learning algorithm. proposed solution based on vector instructions effectively ...

We proposed an intensity-based morphological pyramid image registration algorithm. This approach utilizes the global affine transformation model, also considering radiometric changes between images. With the morphological pyramid structure, Levenberg-Marquardt optimization, and bilinear interpolation, this algorithm can be implemented hierarchically and iteratively with capability of measuring,...

A smooth nonlinear system identification method without resorting to on-line parameter estimation is presented. Based on the radial basis function, a signal-dependent ARX (RBF-ARX) model is established to describe the nonlinear system dynamics. Especially, a new structured nonlinear parameter optimization algorithm based on the Levenberg-Marquardt algorithm and the least squares method is propo...

The Al4laoui algorithm is aweighted mean-square-error (MSE) approach to pattern recognition. It employs redundancy, reintroducing the erroneously classified samples to increase the population of their corresponding classes. The algorithm was originally developed for single-layer neural networks. In this paper the algorithm is extended to multilayer neural networks. It is also shown that the app...