This study comprises developing a more appropriate hybrid wavelet-modified GMDH model for forecasting the monthly crude palm oil (CPO) price of Malaysia. In proposed model, complex data CPO is decomposed into different sub series using discrete wavelet transform (DWT) and then it has been linked with modified model. Sigmoid, radial basis, tangent polynomial functions are selected as transfer in...

Dependency of explicit costs index of mining opening on its parameters is modeled. In addition, the problem of structural identification is solved. Models enumeration is realized with the help of group methods of data handling (GMDH). Least-squares and least-modules methods are used for evaluating model parameters. The quality of resulting models is evaluated by the following criteria: (a) rema...

This article deals with the problem of determination of the model uncertainty during the system identification via application of the self-organising group method of data handling (GMDH) neural network. In particular, the contribution of the neural network structure errors and the parameter estimates inaccuracy to the model uncertainty were presented. Knowing these sources and applying the Oute...

Item ranking and selection plays a key role in constructing concise and informative educational tests. Traditional techniques based on the item response theory (IRT) have been used to automate this task, but they require model parameters to be determined a priori of each item and their application becomes more tedious with larger item banks. Machine learning techniques can be used to build data...

Abstract Weirs are one of the most common hydraulic structures used in water engineering projects. In this research, a group method data handling (GMDH) was developed to estimate energy dissipation flow passing over labyrinth weirs with triangular and trapezoidal plans. To compare performance model other types soft computing models, multilayer perceptron neural network (MLPNN) developed. The di...

In this study, it was aimed to develop an accurate forecasting model for the monthly electricity demand of Turkey in medium-term. For purpose, Group Method Data Handling (GMDH)-type Neural Network (NN) approach used structure a nonlinear time-series based model. A large dataset containing considered period 2003-2018. The developed tested 2019/01-2019/11 order determine generalization ability te...

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...

Shear wave velocity (VS) is one of the most important parameters in deep and surface studies estimation geotechnical design parameters. This parameter widely utilized to determine permeability porosity, lithology, rock mechanical parameters, fracture assessment. However, measuring this either impossible or difficult due challenges related horizontal deviation wells difficulty reaching cores. Ar...