Data for: FlotationNet: A hierarchical deep learning network for froth flotation recovery prediction

Published: 5 August 2020| Version 1 | DOI: 10.17632/2vsrjbtfp5.1
Yuanyuan Pu


Data are from a manufacturing froth flotation plant. The first column shows time and date range (from march of 2017 until september of 2017).The second and third columns are quality measures of the iron ore pulp right before it is fed into the flotation plant. Column 4 until column 8 are the most important variables that impact in the ore quality in the end of the process. From column 9 until column 22, we can see process data (level and air flow inside the flotation columns, which also impact in ore quality. The last two columns are the final iron ore pulp quality measurement from the lab.