A technique for dynamic system parameter estimation by using artificialneural-network-like approximators is developed. The technique offers very high speed and high noise immunity. However, in cases where the number of unknown parameters and the estimation accuracy level required are high, the neural network needed to perform the task is rather complex. This causes the training process prohibit...

Iris recognition has been considered as one of the most reliable biometrics technologies in recent years due to its high reliability in person identification. In this paper, an iris recognition system has been proposed. The recognition system relies on four fundamental steps. The first step consists of iris localization using Circular Hough Transform (CHT). In the subsequent step, image is norm...

the spatial distribution of petrophysical properties within the reservoirs is one of the most importantfactors in reservoir characterization. flow units are the continuous body over a specific reservoirvolume within which the geological and petrophysical properties are the same. accordingly, anaccurate prediction of flow units is a major task to achieve a reliable petrophysical description of a...

A method of creating a constitutive model layered rocks based on an artificialneural network (ANN) is reported in this work. The ANN gives implicitconstitutive function ∑ ∑n n1 F( E, ), relating the new state homogenizedstresses n 1 with old Σn and increment homogenized strains. first step to repeatedly run strain- controlled homogenisation onan uni-dimensional finite element periodic cell elas...

in this study, an artificial neural network was developed in order to analyze flexible pavement structure anddetermine its critical responses under the influence of standard axle loading. in doing so, more than 10000four-layered flexible pavement sections composed of asphalt concrete layer, base layer, subbase layer, andsubgrade soil were analyzed under the impact of standard axle loading. pave...

The larger the size of the data, structured or unstructured, the harder to understand and make use of it. One of the fundamentals to machine learning is feature selection. Feature selection, by reducing the number of irrelevant/redundant features, dramatically reduces the run time of a learning algorithm and leads to a more general concept. In this paper, realization of feature selection throug...

Globally, recent research are focused on developing appropriate and robust algorithms to provide a healthcare system that is versatile accurate. Existing malaria models plagued with low rate of convergence, overfitting, limited generalization due restriction binary cases prediction, proneness local minimum errors in finding reliable testing output complexity features the feature space, which bl...

The building sector accounts for more than 70% of thetotal electricity use. Chillers consume 50% electrical energyduring seasonal periods With the growth sectorand climate change, it's essential to develop energy-efficient HVAC systemsthat optimize ever-increasing energy demand. This study aims anenergy consumption prediction model air-cooled chillers using machinelearning algorithms. is done b...