Artificial neural networks (ANN) is an approach to solving different tasks. In this paper we forecast U.S. stock market movements using two types of artificial neural networks: a network based on the Levenberg-Marquardt learning mechanism and a synergetic network which was described by German scientist Herman Haken. The LevenbergMarquardt ANN is widely used for forecasting financial markets, wh...

Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...

Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...

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...

in the present study, computational fluid dynamics (cfd) techniques and artificial neural networks (ann) are used to predict the pressure drop value (δp ) of al2o3-water nanofluid in flat tubes. δp  is predicted taking into account five input variables: tube flattening (h), inlet volumetric flow rate (qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (φ) and nanoparticle diameter (dp ...

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 and bearings. 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 co...

This paper presents overview of applications of artificial neural networks (ANN) in the field of engine development. Various approaches using ANN are highlighted that resulted in better modeling of engine operations. Using ANN we can reduce engine development time. The paper discusses ANN approach, algorithms and importance of architecture. This will also help in advancing ANN research.

hardware-implemented ANN presented framework realization: ! 2 ANN ASICs with binary neurons and analog synapses ! implementing a recurrent Perceptron model ! controlled by an FPGA (framework controller) ! trained by an evolutionary algorithm ! capabale of scaling mapping to resources desired network topology We propose a framework for hardware artificial neural networks (ANN) that allows to map...

Artificial Neural Networks are useful for pattern recognition and also popular as classification mechanisms in medical decision support systems despite the fact that they are unstable predictors An important application of Gene Expression Data is classification of biological samples or prediction of clinical and outcomes. In this paper a method is proposed that combines statistical technique an...

job satisfaction (js) plays important role as a competitive advantage in organizations especially in helth industry. recruitment and retention of human resources are persistent problems associated with this field. most of the researchs have focused on the job satisfaction factors and few of researches have noticed about its effects on productivity. however, little researchs have focused on the ...