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焦炭的质量对高炉冶炼的生产有着重要的影响,为了解决焦炭质量预测问题,提出了基于BP神经网络的质量预测算法,文中详细阐述了该模型的建立过程和实现方法,同时也给出了在进行模型处理的时候数据预处理的方法。利用人工神经网络对非线性问题的模拟能力,构建了焦炭质量预测模型,测试结果表明在100组不同类型的焦炭质量预测分析中,质量预测的精度达到了95%。
In order to solve the problem of coke quality prediction, a quality prediction algorithm based on BP neural network is put forward. The establishment process and realization method of this model are described in detail in this paper. At the same time, The method of data preprocessing during model processing. The coke quality prediction model was constructed by artificial neural network’s ability to simulate nonlinear problems. The test results showed that the accuracy of the quality prediction reached 95% in 100 different types of coke quality prediction analysis.