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 to predict the energy consumption. A low-code algorithmic platform support is provided for the steel industry to achieve energy saving and efficiency improvement.

I. Introduction

It is well known that the steel industry is the world's largest energy-consuming industry, and with the development of science and technology, the overall technological level of the steel industry has improved greatly, but the current energy use efficiency is still very low [1]. At the same time, such high energy consumption and emission problems lead to high production costs and a negative impact on the environment.