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

Gabriella Balacco
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Gabriella Balacco: Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Politecnico di Bari, Via E. Orabona, 4, 70125 Bari, Italy

Energies, 2018, vol. 11, issue 12, 1-17

Abstract: 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.

Keywords: pumps as turbines; artificial neural networks; evolutionary polynomial regression; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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