Performance prediction of hybrid thermoelectric generator with high accuracy using artificial neural networks

2019 ◽  
Vol 33 ◽  
pp. 53-60 ◽  
Author(s):  
Appadurai Anitha Angeline ◽  
Lazarus Godson Asirvatham ◽  
Duraisamy Jude Hemanth ◽  
Jayaraj Jayakumar ◽  
Somchai Wongwises
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Performance Prediction ◽  
Thermoelectric Generator ◽  
High Accuracy ◽  
Artificial Neural

Performance prediction of a RPF-fired boiler using artificial neural networks

2013 ◽  
Vol 38 (8) ◽  
pp. 995-1007 ◽  
Author(s):  
Shishir Kumar Behera ◽  
Eldon R. Rene ◽  
Min Choul Kim ◽  
Hung-Suck Park
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Performance Prediction ◽  
Artificial Neural

scholarly journals Performance Prediction of a Pump as Turbine: Sensitivity Analysis Based on Artificial Neural Networks and Evolutionary Polynomial Regression

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3497 ◽  
Author(s):  
Gabriella Balacco
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Performance Prediction ◽  
Polynomial Regression ◽  
Input Parameter ◽  
Regression Methods ◽  
Reverse Mode ◽  
Evolutionary Polynomial Regression ◽  
Starting Point ◽  
Artificial Neural

The research of a general methodology to predict the pump performance in a reverse mode, knowing those of a pump in a direct mode, is a question that is still open. The scientific research is making many efforts toward answering this question, but at present, there is still not much clarity. This consideration has been the starting point of this research that thanks to artificial neural networks and evolutionary polynomial regression methods have tried to investigate and define the real weight of every input parameter, representing the efficiency of a pump in a direct way, on the output parameters, and representing efficiency of a pump used like a turbine.

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