NDLI: Data-driven modeling for fixed-bed intermittent gasification processes by enhanced lazy learning incorporated with relevance vector machine

Content Provider	IEEE Xplore Digital Library
Author	Shida Liu Zhongsheng Hou Chenkun Yin
Copyright Year	2014
Description	Author affiliation: Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China (Shida Liu; Zhongsheng Hou; Chenkun Yin)
Abstract	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 the complexity of UGI gasification process, especially severe changes in the temperature versus infrequent manipulation of the gasifier and noise in the temperature data collected from practical fields. Noticing that the changes of some input variables of UGI gasification process are small but impactful, a novel weighted-neighbour selection method, which is based on minimizing dynamic cost functions for different outputs coordinately, is adopted to enhance the lazy learning approach. The sparseness and short test time of RVM is fully utilized in design and implementation of the proposed online modeling algorithm under the Bayesian learning framework. The effectiveness of ELL-RVM for modeling UGI gasification processes is verified by a series of experiments based on the data collected from practical fields.
Starting Page	1019
Ending Page	1024
File Size	452421
Page Count	6
File Format	PDF
ISBN	9781479928378
DOI	10.1109/ICCA.2014.6871060
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Temperature measurement Cost function Vectors Mathematical model Training MIMO relevance vector machine Data-driven modeling UGI gasifier enhanced lazy learning
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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