This chapter first optimizes the structural parameters of the E-DUC dilution system based on the ratio of dilution water intake to the flow rate of the full tailings before dilution. Taking into account the fabric and flocculation effects of the feedwell, the average diameter of the tailings flocs at the outlet of the feedwell, the uniformity index on the circumference of the outlet of the feedwell, and the effective flow rate of the feedwell were used as evaluation indicators for the flocculation behavior of the full tailings. The effects of feed speed, the diameter of the feedwell, height of the feedwell, width of the annular baffle, and spiral angle of the spiral mixing groove on the flocculation and fabric effects were analyzed. Orthogonal experimental design was applied to simulate and optimize the parameters with flocculation and fabric effects as the objectives. Finally, based on the flocculation behavior of the full tailings, a BP neural network combined with overall desirability (OD) function was applied to perform multi-parameter multi-objective optimization of the feedwell based on the flocculation behavior of the full tailings.