Bending Force of Hot Rolled Strip Based on Improved Whale Optimization Algorithm and Twinning Support Vector Machine

Bending control is one of the main methods shape for hot rolled plate. However, existing bending force setting models based on traditional mathematical are complex and have low accuracy, which leads to poor strip exit shapes. Aiming at problem algorithm, an improved whale swarm optimization algorithm twin support vector machine-based model steel (LWOA-TSVR) proposed. Based rolling field production data a plant, research group established prediction by using nonlinear approximation ability machine. The introduction Levy flight improvement improves generalization ability, convergence speed with help coefficient vectors, solves random selection parameters optimizes jump out local optimum. actual database, hit rate proposed method reaches 91% (from ?5 5 KN), fully meets requirements detection accuracy line. not only able overcome search obtain global optimal solution, but also has advantages fast higher accuracy. A comparison machines algorithms shows that higher. experimental results show this over in terms improving providing theoretical guidance practical settings.