Detection of total iron content based on improved extreme learning machine

Abstract

The average grade of iron ore is low in China, and it is significant for the effective utilization of iron ore to obtain grades. In the paper, the high-precision model was constructed based on the spectrum of hematite and the multiple hidden layers extreme learning machine with random values and dense connection, which took the output of all previous layers as the input of each hidden layer. It has achieved high precision during the detection of the total iron content for hematite, which meets the requirements for the construction and development of new green and intelligent mines.

Keywords:

• Dense connection
• extreme learning machine
• hematite
• spectrum

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [Grant 52074064]; in part by the National Key Research and Development Program of China [2020AAA0109203]; in part by the Natural Science Foundation of Science and Technology Department of Liaoning Province [2021-BS-054]; and in part by the Fundamental Research Funds for the Central Universities, China [Grants N2104026, N2018008, and N2001002].