In this paper our aim is to study how an ensemble of classifiers can improve the performance of a machine learning technique for cell phenotype image classification. We want to point out some of the advantages that an ensemble of classifiers permits to obtain respect a stand-alone method. Finally, the preliminary results on the 2D-HeLa dataset, obtained by the fusion between a random subspace o...

An approach based on the consideration that electrocardiogram (ECG) signals are chaotic signals was presented for automated diagnosis of electrocardiographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. Recurrent neural network (RNN) was implemented and used as basis for detection of variabilities of ECG sign...

forecasting of temperature is a very important in meteorology. air temperature prediction is of a concern in environment, industry and agriculture. temperature with precipitation are important factors in meteorology and are used in classification of climate. in this paper we want to predict average monthly temperature for chosen station of isfahan province. an artificial neural network is a pow...

The quality of electric power has been a constant topic of study, mainly because inherent problems to it can lead to great economic losses, especially in industrial processes. Among the various factors that affect power quality, those related to transients originating from capacitor bank (CB) switching in the primary distribution systems must be highlighted. This paper ‎presents an Artificial N...

The aim of the study is to find right architecture NARX neural network, in order perform daily prediction maximum wind speed Laayoune city. We relied on Levenberg-Marquardt optimization algorithm. RMSE error metric showed that NARX-SP outperforms NARX-P.

in this study, a three–layer artificial neural network (ann) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. a total of 455 data points were collected from 13 data sources to develop the ann model. superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of t...

among the different classes of physical properties of foods, color is considered the most important visual attribute in quality perception. consumers tend to associate color with quality due to its good correlation with physical, chemical and sensorial evaluations of food quality. this study used an inexpensive method to predict sweet cherries color parameters by combining image processing and ...

Abstract The aim of the research is to develop a neural network model predict mechanical strength AZ31 magnesium alloy in addition with Calcium. This would help researchers or academicians fabricate AZ31+x wt. % Ca which finds more importance making biodegradable implants orthopedic surgery. As yield human bone lies between 104.9 – 114.3 MPa whereas for pure Mg it very lesser, needed make alloy...