Forecasting of a ground-coupled heat pump performance using neural networks with statistical data weighting pre-processing

By Hikmet Esen, M. Inalli, A. Şengur, Mehmet Esen. 2008

237 citations recorded by the source corpus.

Subfields: Building and Construction, Mechanical Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/ceeccfe2c4cec425d0ac1cfdf1126ecc98dde5aa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. M. Mohanraj
2. S. Jayaraj
3. C. Muraleedharan

In Mechanical Engineering

1. M. Mohanraj
2. S. Jayaraj
3. C. Muraleedharan

In Renewable Energy, Sustainability and the Environment

1. M. Mohanraj
2. S. Jayaraj
3. C. Muraleedharan

Citations in the corpus

• Applications of artificial neural networks for thermal analysis of heat exchangers – A review (2015, background): “(vii) MLFFN with statistical data weighting pre-processing reduces the number of training data [215].”