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...

Transition Initiation Sites (TIS) prediction is a challenging problem in computational biology. In the literature TIS is predicted using various machine learning techniques such as Neural Network (NN), Support Vector Machine, etc. We have applied Principal Component Analysis (PCA) to remove highly correlated features which improves the performance in terms of time and accuracy. In this paper we...

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...

In this research we concentrate on developing a system dynamics (SD) model for county cycle economy research. We analyze the causality of the county cycle economy system, set up a set of formulations based on the use of group method of data handling (GMDH), then build a system dynamics model to simulate the evolving process of this county system. Through this model and simulation, we get a seri...

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.

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...

in the present study, computational fluid dynamics (cfd) techniques and artificial neural networks (ann) are used to predict the pressure drop value (δp ) of al2o3-water nanofluid in flat tubes. δp  is predicted taking into account five input variables: tube flattening (h), inlet volumetric flow rate (qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (φ) and nanoparticle diameter (dp ...

”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...