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A modified lazy learning algorithm combined with a relevance vector machine (MLL-RVM) is presented to address a data-driven modelling problem for a gasification process inside a united gas improvement (UGI) gasifier. During the UGI gasification process, the measured online temperature of the produced crude gas is a crucial aspect. However, the gasification process complexities, especially severe changes...
An enhanced lazy learning approach incorporated with relevance vector machine (ELL-RVM) is proposed for modeling of the fixed-bed intermittent gasification processes inside UGI gasifiers. The online measured temperature of produced crude gas plays a dominant role during gasification processes. However, it is difficult to formulate the dynamics of gasifier's temperature via first principles due to...
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