Prediction Model of Silicon Content in Hot Metal Using Optimized BP Network

Shu Fang Li; Shi Liang Chu

doi:10.4028/www.scientific.net/AMR.933.206

Paper Titles

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Melt Pool and Single Track Formation in Selective Laser Sintering/Selective Laser Melting
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Leak-Off Coefficient Analysis in Stimulation Treatment Design
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Prediction Model of Silicon Content in Hot Metal Using Optimized BP Network
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Customizing Procedure of Finite Element Analysis for Sheet Metal Forming
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 933Prediction Model of Silicon Content in Hot Metal...

Prediction Model of Silicon Content in Hot Metal Using Optimized BP Network

Abstract:

In the course of systematic modeling, the artificial neural networks method is studied. In allusion to the defect of grads descension of traditional back propagation network algorithms, some improving measures have been taken to determine the optimal prediction and analysis model. These measures include adaptive learning, additive momentum, reasonable selection of drive function, and using genetic algorithm to optimize the input parameters. And to learn and predict the utilization of blast furnace production data, better application result is acquired.

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Periodical:

Advanced Materials Research (Volume 933)

Pages:

206-211

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.933.206

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Online since:

May 2014

Authors:

Shu Fang Li, Shi Liang Chu*

Keywords:

Optimized Neural Network, Prediction Model, Silicon Content in Hot Metal

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* - Corresponding Author

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