MATHEMATICS FOR MACHINE LEARNING: CASE STUDY ON THE MMK IRON & STEEL WORKS
时间  Datetime
2023-06-13 11:00 — 12:00
地点  Venue
会议室(703)
报告人  Speaker
Dmitrii Muravev
单位  Affiliation
Mathematical modelling department of MMK IRON AND STEEL WORKS
邀请人  Host
Sergei Kalmykov
备注  remarks
报告摘要  Abstract

The presentation is devoted to the aspects of the machine learning (ML) application by supporting different fields of mathematics.  We provide a short overview of the mathematical group, which carries out the studies for the MMK group, which is the largest steel manufacturer in the Russian Federation. Then, we show the business value of the application of mathematical modeling for the metallurgy industry.  Moving from a short overview of the group, we discuss why machine learning is related to mathematics. Furthermore, the different case studies on the ML methods are presented. The first case study shows how the Decision trees (Classification method) could support the decision-making process on the surface control of the steel slabs. The second investigation is based on the application of Gradient boosting (Ensemble models) to perform the internal certification of the steel products. Finally, the hybrid Autoregression & Natural processing model (Deep Learning) is presented to predict the values of the quotation of the hot rolled coils.
--
FROM 211.161.245.*