The study proposes a novel approach to automate classifying Chest X-ray (CXR) images of COVID-19 positive patients. All acquired have been pre-processed with Simple Median Filter (SMF) and Gaussian (GF) kernel size (5, 5). better filter is then identified by comparing Mean Squared Error (MSE) Peak Signal-to-Noise Ratio (PSNR) denoised images. Canny's edge detection has applied find the Region I...

abstract in the present study, agricultural sector import was forecasted by using the econometric and the ann methods. import data from 1971 to 2004 and 2004-2009 was used for forecasting, network training and testing forecast accuracy, respectively. the results shown that feed-forward neural network has much less error and better performance than the arima and the var methods. on the basis of ...

In this study, the use of the three-layer feed forward neural network has been investigated for estimating of infinite dilute diffusion coefficient ( D12 ) of supercritical fluid (SCF), liquid and gas binary systems. Infinite dilute diffusion coefficient was spotted as a function of critical temperature, critical pressure, critical volume, normal boiling point, molecular volume in normal boilin...

Power quality disturbances (PQD) degrades the of power. Detection these PQDs in real time using smart systems connected to power grid is a challenge due integration energy generation units and electronic devices. Deep learning methods have shown advantages for PQD classification accurately. events are non-stationary occur at discrete events. Pre-processing signal dual tree complex wavelet trans...

ECG (Electrocardiogram) performs classification using a machine learning model for processing different features in the signal. The electrical activity of heart is computed with signal library. key issue handling signals an estimation irregularities to evaluate health status patients. impulse waveform specialized tissues cardiac diseases. However, comprises difficulties associated derive certai...

Data-driven flow forecasting models, such as Artificial Neural Networks (ANNs), are increasingly used for operational flood warning systems. In this research, we systematically evaluate different machine learning techniques (random forest and decision tree) compare them with classical methods of the NAM rainfall run-off model Vésubie River, Nice, France. The modeled network is trained tested us...

Abstract Natural fractures play an essential role in the characterization and modeling of hydrocarbon reservoirs. Modeling fractured reservoirs requires understanding fracture characteristics. Fractured zones can be detected by using seismic data, petrophysical logs, well tests, drilling mud loss history core description. In this study, feed-forward neural networks (FFNN), cascade feed forward ...

a neural network with feed forward topology and back propagation algorithm was used to investigate the effect of composition on mechanical properties in api x65 microalloyed steel (used in manufacturing of large diameter pipes). experimental data was obtained by cutting 100 specimens from pipes manufactured in industrial scale (with similar heats and manufacturing processes). the chemical analy...