Prediction of Ferrous Scrap Price: Neural Network Model Application

被引：1

作者：

Panachev, A. A. ^{[1
]}

Komotskiy, E. I. ^{[1
]}

Berg, D. B. ^{[1
]}

Atanasova, T. B. ^{[2
]}

Khorev, O. E. ^{[1
]}

机构：

[1] Ural Fed Univ, Mira 19, Ekaterinburg 620002, Russia

[2] Varna Univ Econ, Varna 9002, Bulgaria

来源：

INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2018 (ICCMSE-2018) | 2018年 / 2040卷

关键词：

artificial neural network; scrap prices; machine learning; forecasting;

D O I：

10.1063/1.5079111

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Today, scrap prices are one of the key factors not only for the stage of production planning, but also for the market analysis. The problem of the scrap prices forecasting in the metallurgical industry is particularly acute. In this article, the authors use a neural network approach to build a model that allows solving this problem. The obtained results show that proposed model provides the forecasting of the future ferrous scrap price fluctuations with high enough accuracy.

引用

页数：4

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