A hybrid algorithm based on extremal optimization(EO)with adaptive lévy mutation and information fashion algorithm(EOIFA)was proposed in this paper.It applied the idea of combination mechanism of global and local search.In the process of the global search

IFA is an evolutionary algorithm based on the difference in group that can quickly approach an approximate optimal solution.EO has powerful local search capability.During the local search

it helps IFA out of local maximum points by selecting the approximate solution of the worst element to proceed adaptive lévy mutation.The EOIFA is applied to train artificial neural network(NN)to construct a practical soft-sensor of removal efficiencies for supercritical water oxidation.The obtained results indicate that the new method proposed by this paper is feasible and effective.