A Moving Window Double Locally Weighted Extreme Learning Machine on an Improved Sparrow Searching Algorithm and Its Case Study on a Hematite Grinding Process
Abstract:In this paper, a double locally weighted extreme learning machine model based on a moving window is developed to realize process modeling. To improve model performances, an improved sparrow-searching algorithm is proposed to optimize the parameters of the proposed model. The effectiveness of the proposed model and algorithm are verified by data from a hematite grinding process. The experimental results show that the proposed algorithm can significantly improve the global search ability and convergence speed in… Show more
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