The safety of power transmission systems in wind turbines is crucial to the turbine’s stable operation and has attracted a great deal attention condition monitoring farms. Many different intelligent schemes have been developed detect occurrence defects via supervisory control data acquisition (SCADA) data, which most commonly applied system turbines. Normally, artificial neural networks are est...

Different variables affect the performance of the Stirling engine and are considered in optimization and designing activities. Among these factors, torque and power have the greatest effect on the robustness of the Stirling engine, so they need to be determined with low uncertainty and high precision. In this article, the distribution of torque and power are determined using experimental data. ...

In this paper, we proposed a novel hybrid group method of data handling least squares support vector machine (GLSSVM) algorithm, which combines the theory a group method of data handling (GMDH) with the least squares support vector machine (LSSVM). With the GMDH is used to determine the inputs of LSSVM method and the LSSVM model which works as time series forecasting. The aim of this study is t...

The group method of data handling technique (GMDH) and Box-Jenkins methods are two wellknown time series forecasting of mathematical modeling. In this paper, we introduce a hybrid modeling which combines the GMDH method with the Box-Jenkins method to model time series data. The Box-Jenkins method was used to determine the useful input variables of GMDH method and then the GMDH method which work...

Neural networks (NN) are a relatively new option to model growth in animal production systems. One self-organizing submodel of artificial NN is the group method of data handling (GMDH)-type NN. The use of such self-organizing networks has led to successful application of the GMDH algorithm over a broad range of areas in engineering, science, and economics. The present study aimed to apply the G...

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...

Agile software development is now accepted as a superior alternative to conventional methods of software development, because of its inherent benefits like iterative development, rapid delivery and reduced risk. Hence, the industry must be able to efficiently estimate the effort necessary to develop projects using agile methodology. For this, different techniques like expert opinion, analogy, d...

In this paper, lift and drag coefficients were numerically investigated using NUMECA software in a set of 4-digit NACA airfoils. Two metamodels based on the evolved group method of data handling (GMDH) type neural networks were then obtained for modeling both lift coefficient (CL) and drag coefficient (CD) with respect to the geometrical design parameters. After using such obtained polynomial n...

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...

Agile Software development has become famous in industries and replacing the traditional methods of software development. A correct estimation of effort in this concept still remains an argument in industries. Thus, the industry must be able to estimate the effort necessary for software development using agile methodology. For estimating effort different types of neural-networks Probabilistic N...