Modeling of heat transfer and fluid flow characteristics of helicoidal double-pipe heat exchangers using Adaptive Neuro-Fuzzy Inference System (ANFIS)

By M. Mehrabi, S. M. Pesteei. 2011

69 citations recorded by the source corpus.

Subfields: Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/0f32c037b34bebc5a32072f4b8b951e2b9e95fd8

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

Citations in the corpus

• Prediction of MEUF process performance using artificial neural networks and ANFIS approaches (2012, background): “pi, qi and ri are designing parameters which are obtained during the learning process [32].”
• Applications of artificial neural networks for thermal analysis of heat exchangers – A review (2015, methodology): “ANFIS predictions of heat exchanger performance were found to be better when compared to MLFFN as reported by many researchers [23,24,64,77,96,98,113,118,136,157].”