Abstract: In this paper, feed-forward recurrent neural networks (RNNs) with a single hidden layer and trained by using a back-propagation learning algorithm are studied and developed for the simulation ...

Abstract: The error is very severe and, in my opinion, negatively affects the quality of the whole paper, since it causes a misunderstanding of the technical content presented.

Abstract: In recent years, transient response analysis of energy systems is becoming more and more important in optimizing plant operation and control. Furthermore, dynamic analyses are also used to ...

Abstract: In the paper, self-adapting models capable of reproducing time-dependent data with high computational speed are investigated. The considered models are recurrent feed-forward neural networks (RNNs) ...

Abstract: The paper deals with the development of a nonlinear one-dimensional modular dynamic model for the simulation of transient behavior of compression systems. The model is based on balance equations ...

Abstract: Gas turbine operating state determination consists of the assessment of the modification due to deterioration and fault of performance and geometric data characterizing machine components. One of ...

Abstract: In the paper, neural network (NN) models for gas turbine diagnostics are studied and developed. The analyses carried out are aimed at the selection of the most appropriate NN structure for ...

Abstract: In the paper, neuro-fuzzy systems (NFSs) for gas turbine diagnostics are studied and developed. The same procedure used previously for the setup of neural network (NN) models (, , , and , ...

Abstract: The correct form of the equation which defines ηC (reported on p. 10, first column, line 2 of the printed version) is the following:ηC=h(T0(n+1)s)−h(T01)h(T0(n+1))−h(T01)

Abstract: The process, which includes production, collection, carriage, and transformation of biomass into renewable fuels and then into energy (both electrical and thermal), involves a large number of ...