© 2015, Springer Science+Business Media New York. A neural-network model allowing for extraction of new knowledge from experimental data is developed on the basis of studies using modern computer technology. Prediction of an output parameter (relative change in coefficient of thermal conductivity) with a relative error of 4% on a network previously trained by means of a knowledge base is demonstrated. Some features and laws of the heat transfer of benzene in an electric field are established
• Thermal conductivity of aqueous solution is predicted with artificial neural network • A feed forw...
The flow and heat transfer characteristics in a nuclear power plant in the event of a serious accide...
In this paper we report results for the prediction of thermodynamic properties based on neural netwo...
© 2015, Springer Science+Business Media New York. A neural-network model allowing for extraction of ...
Widespread application of a neural network has been obvious in many fields of chemical engineering o...
This work presents a literature survey of the available experimental data regarding the thermal cond...
Artificial neural network was used to predict the thermal conductivity of various fruits and vegetab...
This study presents an application of artificial neural networks (ANNs) to predict the heat transfer...
Artificial neural network (NN) is an alternative way (to conventional physical or chemical based mod...
In the present study, estimation and prediction of thermal conductivity (knf) of functionalized Grap...
The results of neural network modeling of average heat transfer in the channels of exchangers with s...
The fact that the properties of thermoelectric materials are to be estimated with Artificial Neural ...
The mass and heat transfer processes are, in the last period, important subjects in the cooling and ...
Abstract. Two different artificial neural networks (NN) are used for estimating a time dependent bou...
In this paper we report results for the prediction of thermodynamic properties based on neural netwo...
• Thermal conductivity of aqueous solution is predicted with artificial neural network • A feed forw...
The flow and heat transfer characteristics in a nuclear power plant in the event of a serious accide...
In this paper we report results for the prediction of thermodynamic properties based on neural netwo...
© 2015, Springer Science+Business Media New York. A neural-network model allowing for extraction of ...
Widespread application of a neural network has been obvious in many fields of chemical engineering o...
This work presents a literature survey of the available experimental data regarding the thermal cond...
Artificial neural network was used to predict the thermal conductivity of various fruits and vegetab...
This study presents an application of artificial neural networks (ANNs) to predict the heat transfer...
Artificial neural network (NN) is an alternative way (to conventional physical or chemical based mod...
In the present study, estimation and prediction of thermal conductivity (knf) of functionalized Grap...
The results of neural network modeling of average heat transfer in the channels of exchangers with s...
The fact that the properties of thermoelectric materials are to be estimated with Artificial Neural ...
The mass and heat transfer processes are, in the last period, important subjects in the cooling and ...
Abstract. Two different artificial neural networks (NN) are used for estimating a time dependent bou...
In this paper we report results for the prediction of thermodynamic properties based on neural netwo...
• Thermal conductivity of aqueous solution is predicted with artificial neural network • A feed forw...
The flow and heat transfer characteristics in a nuclear power plant in the event of a serious accide...
In this paper we report results for the prediction of thermodynamic properties based on neural netwo...