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在研究燃煤煤灰成分与其变形温度之间关系的基础上,提出了煤灰变形温度模拟退火支持向量机的预测模型。该模型将煤灰中的10个氧化物成分作为输入量,煤灰的变形温度作为输出量。用某电厂实测数据对模型进行了校验,结果表明,此方法是合理有效的,经模拟退火算法优化后的支持向量机模型可实现对变形温度较精确的预测。同时依据本模型及面向对象的高级语言,开发了相应的预测评判系统。
Based on the study of the relationship between coal ash content and its deformation temperature, a prediction model of simulated annealing support vector machine with coal ash deformation temperature is proposed. The model takes 10 oxides in coal ash as input and the deformation temperature of coal ash as output. The model is verified by the measured data from a power plant. The results show that this method is reasonable and effective. The SVM model optimized by simulated annealing algorithm can predict the deformation temperature more accurately. At the same time, based on this model and object-oriented high-level language, the corresponding predictive and judgment system has been developed.