Introduction to artificial neural networks.

By Enzo Grossi, Massimo Buscema. European Journal of Gastroenterology and Hepathology, 2007

387 citations recorded by the source corpus.

Subfields: Applied Mathematics, Artificial Intelligence, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/5d7b5d0781f0b92fa7312c51ea8a29833a5b7dbf

How researchers see this paper

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

In Artificial Intelligence

1. Kamaruzzaman Sopian

Citations in the corpus

• Comparison of prediction methods of PV/T nanofluid and nano-PCM system using a measured dataset and artificial neural network (2018, background): “On the other hand, several researchers are implementing predicting tools for PV and PV/T system performance (Singh et al., 2001; Grossi and Buscema, 2007; Al-Waeli et al., 2017b; Devendiran and Amirtham, 2016; Bajestan et al., 2016).”