Construction of a system for measuring the brain activity (electroencephalogram (EEG)) and recognising thinking patterns comprises significant challenges, in addition to the noise and distortion present in any measuring technique. One of the most major applications of measuring and understanding EGG is the brain-computer interface (BCI) technology. In this paper, ANNs (feedforward back-prop and...

Abstract In this study, modeling of discharge was performed in compound open channels with non-prismatic floodplains (CCNPF) using soft computation models including multivariate adaptive regression splines (MARS) and group method data handling (GMDH), then their results were compared the multilayer perceptron neural networks (MLPNN). addition to total discharge, separation between floodplain ma...

The focus of this research is to introduce the application polynomial neural network group method data handling (GMDH) for first time in regional area New South Wales state Australia. Within context, temperature are modeled assess its projected variation impacts on rainfall depth due climate change. study encompasses six local government areas within state’s Central West region. Stochastic meth...

In the present study, multi-objective optimization of centrifugal pumps is performed at three steps. At the first step, η and NPSHr in a set of centrifugal pump are numerically investigated using commercial software. Two meta-models based on the evolved group method of data handling (GMDH) type neural networks are obtained, at the second step, for modeling of η and NPSHr with respect to geometr...

In the present study, multi-objective optimization of 4-digit NACA airfoils is performed at three steps. At the first step, lift (CL) and drag (CD) coefficient in a set of 4-digit NACA airfoils are numerically investigated using commercial software NUMECA. Two meta-models based on the evolved Group Method of Data Handling (GMDH) type neural networks are obtained, at the second step, for modelin...

Abstract The study aims at forecasting the return volatility of cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method data handling (GMDH-NN) algorithm. used in this is spanning from April 14, 2017, to October 30, 2020, covering 1296 observations. We predict four cryptocurrencies, namely Bitcoin, E...

With the increasing level of intelligence marine engines, there is an demand for online monitoring and NOx emissions have been great concern. In this paper, a simulation model developed based on virtual measurement technology, which can calculate predict current operating state parameters low-speed two-stroke diesel engines. First, calibrated 3D used to design experiments obtain experimental sa...

The prediction of the ultimate bearing capacity of the pile under axial load is one of the important issues for many researches in the field of geotechnical engineering. In recent years, the use of computational intelligence techniques such as different methods of artificial neural network has been developed in terms of physical and numerical modeling aspects. In this study, a database of 100 p...

Among the foremost frequent and vital tasks for hydrologist is to deliver a high accuracy estimation on hydrological variable, which reliable. It essential flood risk evaluation project, hydropower development developing efficient water resource management. Presently, approach of Group Method Data Handling (GMDH) has been widely applied in modelling sector. Yet, comparatively, same tool not vas...