【摘要】 采用改进的人工神经网络算法,开发了40t钢包炉精炼时钢水终点温度预报模型。与传统BP网络算法相比较,改进算法可提高预测速度和精度。生产现场实验表明,传统BP神经网络算法,钢水温度预测误差±5℃的炉次仅为77%,用改进的BP神经网络算法,其误差±5℃的炉次为90%。更多还原

【Abstract】 The prediction model of end point temperature of molten steel refining in a 40 t ladle furnace has been developed bya modified artificial neural network calculation method.Compared with traditional Back-Propagation(BP)network calculation method,the modified artificial calculation method can increase prediction efficiency and precision.The examination in production situ showed that using modified BP artificial neural network calculation method,the heats percentage with ±5 ℃ error of prediction temperature of molten steel was 90%,while using traditional BP artificial neural network calculation method,that with ±5 ℃ error of prediction temperature only 77%.更多还原