基于数据挖掘算法的垂直水冷壁壁温预测模型

Prediction model of vertical water wall temperature using data mining algorithm

结合某电厂垂直水冷壁壁温频繁超温问题,采用垂直水冷壁壁温超温机理和门控神经网络算法(GRU)相融合的方法,建立壁温预测模型,采集电厂历史运行数据,经数据预处理生成数据集,统计与分析预测模型数据训练结果,确定研究与优化方向,提高预测模型的精度和鲁棒性。

Combined with the frequent overtemperature problem of the vertical water wall in power plant,the overtemperature mechanism of vertical water wall and the gated neural network algorithm(GRU) are integrated to establish the prediction model,collect the historical operation data of power plant and perform data preprocessing,based on the statistics and analysis of data training results,develop further research and optimization direction to improve the accuracy and robustness of prediction model.