Background: The artificial neural networks (ANNs) are useful in solving nonlinear processes, without the need for mathematical models of the parameters. Since the relationship between the CT numbers and material compositions is not linear, ANN can be used for obtaining tissue density and composition.Objective: The aim of this study is to utilize ANN for determination of the composition and mass...

Artificial Neural Networks (ANN) have traditionally enjoyed considerable attention in process control applications. Thus, the paper is focused on real system control design using neural networks. The point is to show whether neural networks bring better performances to nonlinear process control or not. Artificial Neural Network is nowadays a popular methodology with lots of practical and indust...

prediction of the heavy metals in the groundwater is important in developing any appropriate remediation strategy. this paper attempts to predict heavy metals (pb, zn and cu) in the groundwater from arak city, using artificial neural network (ann) algorithm by taking major elements (hco3, so4) in the groundwater from arak city. for this purpose, contamination sources in the groundwater were rec...

Evolutionary Artificial Neural Networks (EANN) have been a focus of research in the areas of Evolutionary Algorithms (EA) and Artificial Neural Networks (ANN) for the last decade. In this paper, we present an EANN approach based on pareto multi-objective optimization and differential evolution augmented with local search. We call the approach Memetic Pareto Artificial Neural Networks (MPANN). W...

in this paper, a new approach of modeling for artificial neural networks (ann) models based on the concepts of ann and fuzzy regression is proposed. for this purpose, we reformulated ann model as a fuzzy nonlinear regression model while it has advantages of both fuzzy regression and ann models. hence, it can be applied to uncertain, ambiguous, or complex environments due to its flexibility. in ...

in this paper, a fault diagnosis system based on discrete wavelet transform (dwt) and artificial neural networks (anns) is designed to diagnose different types of fault in gears. dwt is an advanced signal-processing technique for fault detection and identification. five features of wavelet transform rms, crest factor, kurtosis, standard deviation and skewness of discrete wavelet coefficients of...

abstract   background : leukemia is one of the mostcommon cancers in children, comprising more than a third of all childhood cancers. newly affected patients in usa are estimated as 10100cases, and if these cases are diagnosed late or proper treatment is not applied, then it can be mortal. because rapid and proper diagnosis of leukemia based on clinical or medicinal findings (without biopsy) is...

Among artificial intelligence approaches, artificial neural networks (ANNs) and genetic algorithm (GA) are widely applied for modification of materials property in engineering science in large scale modeling. In this work artificial neural network (ANN) and genetic algorithm (GA) were applied to find the optimal conditions for achieving the maximum hardness of Al6061 reinforced by multiwall car...

Ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment Canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (ANNs) are introduced to obtain improved regional low-flow estimates at ungauged sites. A multilayer perceptron (MLP) network is used to identify the funct...