Prediction of the production rate of the cutting dimensional stone process is crucial, especially when chain saw machines are used. The cutting dimensional rock process is generally a complex issue with numerous effective factors including variable and unreliable conditions of the rocks and cutting machines. The Group Method of Data Handling (GMDH) type of neural network and Radial Basis Functi...

The evaluation of road safety is a critical issue having to be conducted for successful management in transport systems, whereas considered transportation systems as challenging task according the dynamic this and presence large number effective parameters on safety. Therefore, analysis important contributing factors affecting vehicles involved crashes play key role increasing efficiency For pu...

nowadays, due to increasing the complexity of ic engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. in this paper four network base...

Accurate forecasting of electricity load is one of the most important issues in the electricity industry. It is essential part of an efficient power system planning and operation. Due to the limited generic structure of conventional group method of data handling (GMDH) network (quadratic twovariable polynomial), it tends to produce an exceedingly complex network when it comes to highly nonlinea...

In the present study, multi-objective optimization of Forward-Curved (FC) blade centrifugal fans is performed in three steps. In the first step, Head rise (HR) and the Head loss (HL) in a set of FC centrifugal fan is numerically investigated using commercial software NUMECA. Two meta-models based on the evolved group method of data handling (GMDH) type neural networks are obtained, in the secon...

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...

In this chapter we describe new neural-network techniques developed for visual mining clinical electroencephalograms (EEGs), the weak electrical potentials invoked by brain activity. These techniques exploit fruitful ideas of Group Method of Data Handling (GMDH). Section 2 briefly describes the standard neural-network techniques which are able to learn well-suited classification modes from data...

A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...