一种融入GRA的生物质气化焦油脱除LSSVM建模方法

A LSSVM MODELING MEHTOD BASED ON GRA FOR THE REMOVAL PROCESS OF BIOMASS ASIFICATION TAR

提出一种融入灰色关联度分析(GRA)的生物质气化焦油脱除最小二乘支持向量机(LSSVM)建模方法。该模型考虑生物质气化焦油脱除过程影响因素的多样性和不确定性,通过试验数据的GRA分析,提取气化焦油脱除过程的强相关因素作为模型训练样本,建立生物质气化焦油脱除过程GRA-LSSVM模型,可有效克服传统建模方法对所有数据样本等同处理而造成的模型精度不高的不足。对松木屑气化焦油脱除过程建模分析,验证模型的有效性和准确性。

A least square support vector machine （LSSVM） modeling method based on GRA for the removal process of biomass gasification tar was put forward. The model takes the influencing factors of diversity and uncertainty in the biomass gasification tar removal process into account and through analyzing the experimental data by GRA, factors which have great influences on tar removal process are extracted to be the training sample of the model so that the GRA-LSSVM model for the biomass gasification tar removal process is established which effectively overcome the deficiency of model accuracy in traditional modeling method for all data samples equal treatment. The modeling analysis of the pine crumbs in the gasification tar removal process, verifying the effectiveness and accuracy of the model.