Notice of RetractionRobust kernel PLS based soft sensing for component concentrations in sodium aluminate solution

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

The component concentrations in sodium aluminate solution are very important in the process of alumina production, they represents the product quality. At present they can not be measured online, so the optimal operation is hardly to be achieved. To deal with this problem and based on the character of process industry data, we propose a RKPLS (Robust Kernel Partial Least Squares) soft sensing method by combining robust algorithm and kernel transformation to predict the component concentrations in sodium aluminate solution. Industry experiments are conducted in the alumina production process and the results show the effectiveness of this method.