@inproceedings{3f3b9951e7b1474b915a1fba32344d44,
title = "Temperature prediction in electric arc furnace with neural network tree",
abstract = "This paper presents a neural network tree regression system with dynamic optimization of input variable transformations and post-training optimization. The decision tree consists of MLP neural networks, which optimize the split points and at the leaf level predict final outputs. The system is designed for regression problems of big and complex datasets. It was applied to the problem of steel temperature prediction in the electric arc furnace in order to decrease the process duration at one of the steelworks.",
author = "Miros{\l}aw Kordos and Marcin Blachnik and Tadeusz Wieczorek",
year = "2011",
doi = "10.1007/978-3-642-21738-8\_10",
language = "English",
isbn = "9783642217371",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 2",
pages = "71--78",
booktitle = "Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings",
address = "Germany",
edition = "PART 2",
note = "21st International Conference on Artificial Neural Networks, ICANN 2011 ; Conference date: 14-06-2011 Through 17-06-2011",
}