Mine reclamation based on remote sensing information and error compensation extreme learning machine

Abstract

In view of the many shortcomings of traditional copper ore detection methods, this paper proposes a new method for copper ore content detection, which is to detect copper ore content through spectral information. And we propose an error compensation extreme learning machine model. Using the error compensation extreme learning machine and the spectral information of the copper ore can quickly and accurately identify the copper content in the copper ore. Finally, the satellite remote sensing data were simulated, and the copper content distribution in the mining area was obtained. This provides guidance for future mining, reclamation and ore prospecting.

Keywords:

• Copper mine
• extreme learning machine
• land reclamation
• remote sensing

Additional information

Funding

This work was supported by National Natural Science Foundation of China under Grand 52074064, Grant 51674063, Grant 61203214, in part by the Fundamental Research Funds for the Central Universities, China, under Grant N180404012, Grant N182608003, N2001002, N182410001; in part by the Fundamental Research Funds for Liaoning Natural Science Foundation, China, under Grant 2019-MS-120.