@inproceedings{776ab32c68c34ee7b1ed8965837e576f,
title = "Application of Artificial Neural Network to Predict the Thermal and Thermomechanical Behavior of Refractory Linings",
keywords = "artificial neural network, refractory lining, steel ladle, thermomechanical behavior",
author = "Aidong Hou and Shengli Jin and Dietmar Gruber and Harald Harmuth",
note = "Funding Information: The Competence Center for Excellent Technologies research programme in “Advanced Metallurgical and Environmental Process Development” (K1-MET) is supported by the Austrian Competence Centre Programme COMET (Competence Center for Excellent Technologies) with funds from the Federal Ministry for Transport, Innovation and Technology, the Federal Ministry of Economy, the provinces of Upper Austria and Styria, the Styrian Business Promotion Agency, and the Tyrolian Future Foundation. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Joint Conference on Neural Networks, IJCNN 2022 ; Conference date: 18-07-2022 Through 23-07-2022",
year = "2022",
doi = "10.1109/IJCNN55064.2022.9891901",
language = "English",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "Institute of Electrical and Electronics Engineers",
booktitle = "2022 International Joint Conference on Neural Networks, IJCNN 2022 - Proceedings",
address = "United States",
}