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Using BP Neural Network to Predict the Sinter Comprehensive Performance: Feo and Sinter Yield

机译:使用BP神经网络预测烧结综合性能:FEO和烧结产量

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摘要

Sinter is the main raw material for ironmaking. It is very important to control sinter chemical composition and comprehensive performance. In this paper, a predictive system for sinter chemical composition FeO and the sinter yield was established based on BP neural network, which was trained by actual production data. The MATLAB m file editor was used to write code directly in this paper.The application results show that the prediction system has high accuracy rate, stability and reliability, the sintering productivity was improved effectively.
机译:烧结是炼铁的主要原料。控制烧结化学成分和综合性能非常重要。本文基于BP神经网络建立了一种用于烧结化学成分Feo和烧结产量的预测系统,由实际生产数据训练。 Matlab M文件编辑器用于直接编写代码。应用结果表明,预测系统具有高精度,稳定性和可靠性,有效提高了烧结生产率。

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