Study on Activity Prediction of Slag in Material Engineering with Software Analysis Based on GA-BPNN

Abstract:

Genetic algorithm-back propagation neural network (GA-BPNN) was used for activity prediction of slag, then activity prediction software of slag was developed by Matrix Laboratory (Matlab) and Microsoft visual C++ (VC++), and activity database of slag was established. The software is simple operation and activity of slag can be predicted accurately, almost activity of slag in the condition of different temperature and composition of slag system can be predicted. The plenty of activity data was collected by the database of software, therefore, more accurate activity data for thermodynamic and dynamics calculation of metallurgist were provided by software. The software lays a good foundation for producing more advanced steel materials.

• Periodical: Advanced Materials Research (Volume 600)
• Pages: 208-213
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.600.208
• Online since: November 2012
• Authors: Ying Zhuang, Zhou Hua Jiang, Yang Li
• Keywords: Activity, GA-BPNN, Material Engineering, Slag, Software

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