<p>In this paper certain type of biometric measurements has been used to identify the cone beam computed tomography (CBCT) radiograph subject in a fast and reliable way. Where CBCT person is as data stored database for later use person’s recognition process. The aim research various stages preprocessing operations obtain clearest possible image that will help us identification process mor...

Swarm Intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment causing coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. Thi...

This paper introduces hybridization of particle swarm optimization (PSO) with genetic algorithm (GA) denoted as PSO+GA provides an efficient approach which is used to solve non linear chaotic datasets. The proposed algorithm employed in probabilistic neural network(PNN) which is a variant of radial basic function artificial neural network (RBFANN) for finding precise value spread factor for acc...

This paper presents a novel and efficient method to estimate the equivalent circuit parameters of three-phase induction motor from its manufacturer data for steady state analysis using improved particle swarm optimization (IPSO). The IPSO integrates the particle swarm optimization (PSO) with the chaotic sequences. The optimization problem is based on minimizing the error between the computed pe...

There are some difficulties encountered in the application of fuzzy Radial Basis Function (RBF) neural network. One of them is how to determine the number of hidden rule neurons and another difficulty is about interpretability. In order to overcome these difficulties, we have proposed a fuzzy neural network based on RBF network and takagi-sugeno fuzzy system. We have used a new structure of fuz...

Biogeography-based optimization (BBO) is a new evolutionary optimization algorithm that is based on the science of biogeography. In this paper, BBO is applied to the optimization of problems in which the fitness function is corrupted by random noise. Noise interferes with the BBO immigration rate and emigration rate, and adversely affects optimization performance. We analyse the effect of noise...

Aim at the class electromagnetic algorithm (EM) late for “mining” ability is insufficient, solution precision is not higher, and easy in premature problem, this paper proposes a combination of chaotic map and confined quasi-Newton (L-BFGS) local optimization operator of the chaotic class electromagnetism algorithm. Its main idea is in the late class electromagnetism algorithm using limit domain...

In this study the performance of two popular evolutionary computational techniques (particle swarm optimization and differential evolution) is compared in the task of batch reactor geometry optimization. Both algorithms are enhanced with chaotic pseudo-random number generator (CPRNG) based on Lozi chaotic map. It is depicted the course of the reactor processes dynamical parameters for the best ...

The problem of finding appropriate representations for various is a subject of continued research in the field of artificial intelligence and related fields. In some practical situations, mathematical and computational tools for faithfully modeling or representing systems with uncertainties, inaccuracies or variability in computation should be provided; and it is preferable to develop models th...

To achieve the maximum power from wind in variable-speed regions of turbines (WTs), a suitable control signal should be applied to pitch angle blades. However, available uncertainty modeling WTs complicates calculations these signals. cope with this problem, an optimal controller is suitable, such as particle swarm optimization (PSO). improve performance controller, fractional order PSO (FPSO) ...