A Modified Artificial Neural Network Learning Algorithm for Imbalanced Data Set Problem

The main objective of reheating furnace is to heat billets up to uniform temperature so as to result in successful rolling process. Since furnace temperature is key point for controlling billet heating, in this paper, a cubic spline is adopted to fitting furnace temperature distribution. Furthermore, a strategy of weighted slide window dynamic compensation and an optimal searching method of eccentric dynamic immune clone algorithm are presented to optimize set point of furnace temperature. Simulations show the effectiveness and efficiency of the proposed strategies.

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