Formulation based on artificial neural network of thermodynamic properties of ozone friendly refrigerant/absorbent couples

By Adnan Sözen, Erol Arcakliogˇlu, M. Özalp. 2005

49 citations recorded by the source corpus.

Subfields: Mechanical Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/b9e35f150799494f96ca8010d07472a19e9f0e44

How researchers see this paper

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

In Mechanical Engineering

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

In Statistical and Nonlinear Physics

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

Citations in the corpus

• Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review (2012, methodology): “[68,69] presented MLFFN approach for predicting he thermodynamic properties of two alternative refrigernt/absorbent couples (methanol–LiBr and methanol–LiCl).”