Modeling and 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 NUMECA. Two metamodels 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 geometrica...

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...

”KnowledgeMiner” was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algorithms to make knowledge extraction systematically, fast, successful and easy-to-use even for large and complex system such as one of the most complex systems: the human. Self-organizing data mining technologies in medical data...

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...

The difficulty in gas price forecasting has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting gas prices however, all of the existing models of prediction cannot meet practical needs. In this paper, a novel hybrid intelligent framework is developed by applying a systematic integration of GMDH neural n...

classification of vegetation according to their species composition is one of the most important tasks in the application of remote sensing in precision agriculture. to prepare an algorithm for such a mandate, there is a need for ground truth. field operation is very costly and time consuming. therefore, some other method must be developed, such as extracting information from the satellite imag...

In this paper, we propose a new constructive method, based on cooperative coevolution, for designing automatically the structure of a neural network for classification. Our approach is based on a modular construction of the neural network by means of a cooperative evolutionary process. This process benefits from the advantages of coevolutionary computation as well as the advantages of construct...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data. In particular we discuss the selection of variables...

Group Method of Data Handling (GMDH)-type neural network algorithms are the heuristic self organization method for the modelling of complex systems. GMDH algorithms are utilized for a variety of purposes, examples include identification of physical laws, the extrapolation of physical fields, pattern recognition, clustering, the approximation of multidimensional processes, forecasting without mo...

The goal of this work is to introduce one of the most successful among recently developed statistical techniques – the support vector machine (SVM) – to the field of corporate bankruptcy analysis. The main emphasis is done on implementing SVMs for analysing predictors in the form of financial ratios. A method is proposed of adapting SVMs to default probability estimation. A survey of practicall...