Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering

Abstract As a major burden of blast furnace, sinter mineral with desired quality performance needs to be produced in sinter plants. The tumbler index (TI) is one of the most important indices to characterize the quality of sinter, which depends on the raw materials proportion, operating system param...

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Bibliographic Details
Main Author: Senhui Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-88755-1
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