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...

In the case of substantial noise, i.e., for inaccurate and incomplete data, the use of the Group Method of Data Handling (GMDH) algorithm leads to sharp and rather deep minimums of dependency of external criterion of accuracy measured on testing sample on the complexity of model structure. This minimum indicates the optimal model. In practice, however, if the noise is just noticeable, i.e., if ...

An Artificial Neural Network is a flexible mathematical structure which is capable of identifying complex nonlinear relationships between input and output data sets. Such Neural Networks have been characterized by passive neurons that are not able to select and estimate their own inputs. In a new approach, which corresponds in a better way to the actions of human nervous system, the connections...

Virtual machines (VMs) dynamic consolidation is effective to improve the utilization of resources and energy efficiency in cloud environment. However, the obligation of providing high quality of service to customers leads to the necessity in dealing with the energy performance trade-off, as aggressive consolidation may lead to performance degradation. Current solutions to the problem of host lo...

in this work, a hybrid gmdh–neural network model was developed in order to predict the moisture content of papaya slices during hot air drying in a cabinet dryer. for this purpose, parameters including drying time, slices thickness and drying temperature were considered as the inputs and the amount of moisture ratio (mr) was estimated as the output. exactly 50% of the data points were used for ...