1. Kandlikar, S. G., Shoji, M. and Dhir, V. K. 1999.Handbook of Phase Change: Boiling and Condensation, 409Philadelphia, PA: Taylor & Francis.
2. Yapo, T., Embrechts, M. J., Cathey, S. T. and Cathey, R. T. L. Jr. “Prediction of critical heat fluex using a hybrid kohonen-backpropagation neural network,”. Intelligent Engineering Systems through Artificial Neural Networks—Proc. Artificial Neural Networks in Engineering (ANNIE'92). St.Louis, Missouri, USA. Vol. 2, pp.853–858.
3. Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks
4. Parametric trends analysis of the critical heat flux based on artificial neural networks
5. Integrating artificial neural networks and empirical correlations for the prediction of water-subcooled critical heat flux