Temperature Prediction in Electric Arc Furnace with Neural Network Tree

被引：0

作者：

Kordos, Miroslaw ^{[1
]}

Blachnik, Marcin ^{[2
]}

Wieczorek, Tadeusz ^{[2
]}

机构：

[1] Univ Bielsko Biala, Dept Math & Comp Sci, Bielsko Biala 2, Willowa, Poland

[2] Silesian Tech Univ, Dept Management & Informat, Katowice, Poland

来源：

ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2011, PT II | 2011年 / 6792卷

关键词：

EAF; MODEL;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：71 / +

页数：2

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