Global method for learning an integrated temperature prediction model in a slab reheating furnace

DOI10.1080/0305215X.2019.1665037OpenAlexW2977442801WikidataQ127179396 ScholiaQ127179396MaRDI QIDQ5059431

No author found.

Publication date: 23 December 2022

Published in: Engineering Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/0305215x.2019.1665037

zbMATH Keywords

SDPSVRreheating furnacetemperature predictionkernel-based learning algorithm

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Uses Software

• SeDuMi
• LIBSVM

Cites Work

• Unnamed Item
• Unnamed Item
• Benchmarking least squares support vector machine classifiers
• Investigation of the slab heating characteristics in a reheating furnace with the formation and growth of scale on the slab surface
• Transient radiative heating characteristics of slabs in a walking beam type reheating furnace
• Optimality conditions and duality theory for minimizing sums of the largest eigenvalues of symmetric matrices
• Support-vector networks
• Modelling and experimental model validation for a pusher-type reheating furnace
• Matrix Analysis
• Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
• Temperature-constrained topology optimization of thermo-mechanical coupled problems

This page was built for publication: Global method for learning an integrated temperature prediction model in a slab reheating furnace