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 study, we introduce and investigate a class of neural architectures of Polynomial Neural Networks (PNNs), discuss a comprehensive design methodology and carry out a series of numeric experiments. PNN is a flexible neural architecture whose structure (topology) is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but becomes generated on t...

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and perturbed by the variation rotor resistance load changes. system has two stages. identification stage, group method data-handling (GMDH) neural network (NN) was designed online modeling IM. GMDH-NN applied to compensate impacts disturbances uncertainties. stability shown Lya...

The group method of data handling (GMDH) and differential evolution (DE) population-based algorithm are two well-known nonlinear methods of mathematical modeling. In this paper, both methods are explained and a new design methodology which is a hybrid of GMDH and DE is proposed. The proposed method constructs a GMDH network model of a population of promising DE solutions. The new hybrid impleme...

The paper deals with the problems of robust fault detection using soft computing techniques, in particular neural networks (Group Method of Data Handling, GMDH), multi-layer perceptron), and neuro-fuzzy networks (Takagi-Sugeno model). The model based approach to Fault Detection and Isolation (FDI) is considered. The main objective is to show how to employ the bounded-error approach to determine...

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...

Increasing of head rise (HR) and decreasing of head loss (HL), simultaneously, are important purpose in the design of different types of fans. Therefore, multi-objective optimization process is more applicable for the design of such turbo machines. In the present study, multi-objective optimization of Forward-Curved (FC) blades centrifugal fans is performed at three steps. At the first step, He...

In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The new improved GMDH is then used to predict currency exchange rates: the US Dollar to the Euros. The performance of the hybrid GMDHs are compared with that of the conventional GMDH. Two performance mea...

0957-4174/$ see front matter 2013 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2013.01.060 ⇑ Tel.: +385 1 4561191. E-mail address: [email protected] The main disadvantage of self-organizing polynomial neural networks (SOPNN) automatically structured and trained by the group method of data handling (GMDH) algorithm is a partial optimization of model weights as the GMDH algorithm optimizes on...