..., a trained ML model may generalize but use incorrect assumptions to predict correct outputs. The motivation of explainable artificial intelligence is to unmask such predictors. Type III ML models, physics-informed machine learning, achieve the same goals as type I and type II ML models, but also couple...

...Kwang-Tzu Yang The use of artificial neural network (ANN), as one of the artificial intelligence methodologies, in a variety of real-world applications has been around for some time. However, the application of ANN to thermal science and engineering is still relatively new, but is receiving ever...

... received by the Heat Transfer Division March 20, 2000; revision received January 8, 2001. Associate Editor: A. Bejan. 20 March 2000 08 January 2001 heat exchangers temperature control model reference adaptive control systems neurocontrollers Artificial Intelligence Control...

... exchangers neural nets heat transfer statistical analysis two-phase flow flow measurement Artificial Intelligence Condensation Convection Heat Transfer Heat Exchangers For the design of a thermal system it is often necessary, for selection purposes, to predict the heat transfer rates...

...J. Ryoo; D. Kaminski; Z. Dragojlovic 01 Dec 1998 03 May 1999 05 12 2007 Artificial Intelligence Computational Fluids Heat Transfer Laminar Numerical Methods Bare W. H. , Mullholland R. J. , and Sofer S. S. , 1990 , “ Design of a Self-Tuning Rule...