BOF Endpoint Prediction Based on Multi-Neural Network Model

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In order to solve the problem that the small and middle converters unable to introduce the sublance detection technology to improve the control precision of endpoint because of the constraints of economy and technology, a method which combine the pedigree cluster and neural network is studied, the pedigree cluster divide the large data sets into several categories, the degree of similarity will be relatively high in each category after division, then train neural model for every category. Finally make predictions. Simulation results show that the multi-neural network model has better prediction results.