BOF Endpoint Prediction Based on Multi-Neural Network Model

You Jun Yue; Ying Dong Yao; Hui Zhao; Hong Jun Wang

doi:10.4028/www.scientific.net/AMM.441.666

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 441BOF Endpoint Prediction Based on Multi-Neural...

BOF Endpoint Prediction Based on Multi-Neural Network Model

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volume 441)

Pages:

666-669

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.441.666

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Online since:

December 2013

Authors:

You Jun Yue, Ying Dong Yao, Hui Zhao, Hong Jun Wang

Keywords:

BOF, Endpoint Prediction, Multi-Neural Network Model, Pedigree Cluster

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