Safety, performance and lifetime of LSB (lithium secondary batteries) are affected by the adhesion of the active material to the electrode substance, and to the electrode deformation and the spring back limit in the electrode manufacturing process. This study explores the optimization process...

Artificial neural network is a powerful tool in the forecast of solar irradiance. In order to gain higher forecasting accuracy, artificial neural network and wavelet analysis have been combined to develop a new method of the forecast of solar irradiance. In this paper, the data sequence of solar...

Calculating global solar irradiation from global horizontal irradiation only is a difficult task, especially when the time step is small and the data are not averaged. We used an Artificial Neural Network (ANN) to realize this conversion. The ANN is optimized and tested on the basis of five...

ANN (artificial neural network) modeling is adopted along GA (genetic algorithm) optimization method in order to investigate spray behavior as function of nozzle and engine variant parameters such as crank-angle, nozzle tip mass flow rate, turbulence, and nozzle discharge pressure. Spray quality...

Surface global solar radiation (GSR) is the primary renewable energy in nature. Geostationary satellite data are used to map GSR in many inversion algorithms in which ground GSR measurements merely serve to validate the satellite retrievals. In this study, a simple algorithm with artificial...

The present work concerns the parametric study and optimization of regenerative Clausius and organic Rankine cycles (ORC) with two feedwater heaters. For the parametric optimization, thermal efficiency, exergy efficiency and specific work are selected as the objective functions, so the mentioned...

An optimized artificial neural network ensemble model is built to estimate daily global solar radiation over large areas. The model uses clear-sky estimates and satellite images as input variables. Unlike most studies using satellite imagery based on visible channels, our model also exploits all...

The objective of this study has been to create an online system for condition monitoring and diagnosis of a combined heat and power plant in Sweden. The system in question consisted of artificial neural network models, representing each main component of the combined heat and power plant,...

The dehumidification process involves simultaneous heat and mass transfer and reliable transfer coefficients are required in order to analyze the system. This has been proved to be difficult and many assumptions are made to simplify the analysis. The present research proposes the use of ANN...

This study deals with artificial neural network (ANN) modeling of a spark ignition engine to predict the engine brake power, output torque and exhaust emissions (CO, CO2, NOx and HC) of the engine. To acquire data for training and testing of the proposed ANN, a four-cylinder, four-stroke test...