Abstract:
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 indust...Show MoreMetadata
Abstract:
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.
Date of Conference: 14-16 June 2024
Date Added to IEEE Xplore: 19 September 2024
ISBN Information:
ISSN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Energy Consumption ,
- Energy Consumption Prediction ,
- Energy Efficiency ,
- Energy Use ,
- Steel Industry ,
- Neural Network ,
- Development Of Technology ,
- Model Performance ,
- Training Set ,
- Deep Learning ,
- Production Process ,
- Time Series Data ,
- Transmission Mode ,
- Energy Utilization ,
- Communication Protocol ,
- Artificial Neural Network Model ,
- Physical Layer ,
- Reduce Production Costs ,
- Smart Meters ,
- High-quality Development ,
- Inception Module
- Author Keywords
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Energy Consumption ,
- Energy Consumption Prediction ,
- Energy Efficiency ,
- Energy Use ,
- Steel Industry ,
- Neural Network ,
- Development Of Technology ,
- Model Performance ,
- Training Set ,
- Deep Learning ,
- Production Process ,
- Time Series Data ,
- Transmission Mode ,
- Energy Utilization ,
- Communication Protocol ,
- Artificial Neural Network Model ,
- Physical Layer ,
- Reduce Production Costs ,
- Smart Meters ,
- High-quality Development ,
- Inception Module
- Author Keywords
