Notice of RetractionOptimized LS_SVM Predictive Control of Gas Outburst Based on Improved PSO

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 dynamic performance of GAS OUTBURST is characterized by huge inertia, long time lag, nonlinear etc, adopting the support vector machines which is based on statistical theory and principle of minimizing structural risk, giving full play to its high-performance modeling ability and good fitting ability could effectively identify the gas outburst model so as to form the predictive model used for predictive control algorithm; The improved particle swarm optimization algorithm based on stochastic global optimization technique is used to solve the predictive control law of the rolling optimization part, and the gas outburst predictive control system based on improved PSO optimization and LSSVM system identification is established. Finally, the simulation result proves the effectiveness of this method and shows that it has better controllability and validity.