Objective (s): Artificial Neural Networks (ANN) are widely used for predicting systems’ behavior. GMDH is a type of ANNs which has remarkable ability in pattern recognition. The aim the current study is proposing a model to predict dynamic viscosity of silver/water nanofluid which can be used as antimicrobial fluid in several medical purposes.Materials and Methods: In order to have precise mode...

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 ...

A feedback Group Method of Data Handling (GMDH)-type neural network algorithm is proposed, and is applied to nonlinear system identification and medical image analysis of liver cancer. In this feedback GMDH-type neural network algorithm, the optimum neural network architecture is automatically selected from three types of neural network architectures, such as sigmoid function neural network, ra...

Neural networks with active neurons which selforganize their structure can use inductive sorting-out GMDH algorithms for their neurons. New threshold type GMDH algorithm with polynomial complexity is developed to decrease computing time in case of large input data sample.

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...

Artificial neural networks (ANNs) have been used increasingly for modelling com-plex hydrological processes. In this paper, we present a self-organizing polynomial neural network (SOPNN) algorithm, which combines the theory of bio-cybernetic self-organizing polynomial (SOP) with the artificial neural network (ANN) approach. With the SOP feature of seeking the best combination of polynomial mode...

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...