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Hottel Zone Physics-Constrained Networks for Industrial Furnaces

This paper investigates a novel approach to improve the temperature profile prediction of furnaces in foundation industries, crucial for sustainable manufacturing. While existing methods like the Hottel Zone model are accurate, they lack real-time inference capabilities. Deep learning methods excel...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Ujjal Kr Dutta, Aldo Lipani, Chuan Wang, Yukun Hu
Format: Artigo
Sprache:Inglês
Veröffentlicht: IEEE 2025-01-01
Schriftenreihe:IEEE Access
Schlagworte:
Extended LSTM (xLSTM)
furnace
Hottel zone method
Kolmogorov-arnold networks (KANs)
long short-term memory (LSTM)
multi-layer perceptrons (MLP)
Online-Zugang:https://ieeexplore.ieee.org/document/10978842/
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