Realization of Low-Code Algorithm for Steel Energy Consumption Prediction

The steel industry is one of the world's highest energy consumption. It is important to improve its energy efficiency. Energy consumption prediction can help steel industry better plan and manage energy use. Based on a low-code development platform, multiple prediction algorithm models are used...

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Bibliographic Details
Published in:IEEE International Conference on Computer Communication and the Internet (Online) pp. 206 - 210
Main Authors: Ji, Wanzhou, Bian, Yunqi, Cai, Hongxia
Format: Conference Proceeding
Language:English
Published: IEEE 14.06.2024
Subjects:
Computational modeling
Deep Learning
Energy conservation
Energy consumption
Energy Consumption Prediction
Energy efficiency
Low-Code Development Platform
Prediction algorithms
Predictive models
Steel industry
ISSN:2833-2350
Online Access:Get full text
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Summary:The steel industry is one of the world's highest energy consumption. It is important to improve its energy efficiency. Energy consumption prediction can help steel industry better plan and manage energy use. Based on a low-code development platform, multiple prediction algorithm models are used to predict the energy consumption. A low-code algorithmic platform support is provided for the steel industry to achieve energy saving and efficiency improvement.
ISSN:2833-2350
DOI:10.1109/ICCCI62159.2024.10674628