Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Shima Khatibisepehr"'
Publikováno v:
IEEE Transactions on Cybernetics. 46:3195-3208
A variational Bayesian approach to robust identification of switched auto-regressive exogenous models is developed in this paper. By formulating the problem of interest under a full Bayesian identification framework, the number of local-models can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76305fe071a186c3756b5af8c394be38
https://doi.org/10.1109/tcyb.2015.2499771
https://doi.org/10.1109/tcyb.2015.2499771
Publikováno v:
AIChE Journal. 61:3232-3248
Process measurements collected from daily industrial plant operations are essential for process monitoring, control, and optimization. However, those measurements are generally corrupted by errors, which include gross errors and random errors. Conven
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b494ac105de3c8774f52484e9c11a793
https://doi.org/10.1002/aic.14864
https://doi.org/10.1002/aic.14864
Publikováno v:
AIChE Journal. 61:518-529
Just-in-time (JIT) learning methods are widely used in dealing with nonlinear and multimode behavior of industrial processes. The locally weighted partial least squares (LW-PLS) method is among the most commonly used JIT methods. The performance of L
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1394a90cbe764ba8391975b1b54bcf03
https://doi.org/10.1002/aic.14663
https://doi.org/10.1002/aic.14663
Autor:
Ramesh Kadali, Aris Espejo, Biao Huang, Swanand Khare, Shima Khatibisepehr, Fangwei Xu, Elom Ayih Domlan
Publikováno v:
Control Engineering Practice. 26:136-150
A definition for the reliability of inferential sensor predictions is provided. A data-driven Bayesian framework for real-time performance assessment of inferential sensors is proposed. The main focus is on characterizing the effect of operating spac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::900ddebcbf14e7b874c0bb967397b9c1
https://doi.org/10.1016/j.conengprac.2014.01.019
https://doi.org/10.1016/j.conengprac.2014.01.019
Publikováno v:
IFAC Proceedings Volumes. 46:277-282
A data-driven Bayesian framework for real-time performance assessment of inferential sensors is proposed. The application of the proposed Bayesian solution does not depend on the identification techniques employed for inferential model development. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b21a3a3274aabe3a61e21a1e68f31a8
https://doi.org/10.3182/20131218-3-in-2045.00093
https://doi.org/10.3182/20131218-3-in-2045.00093
Publikováno v:
Journal of Process Control. 23:1575-1596
In many industrial plants, development and implementation of advanced monitoring and control techniques require real-time measurement of process quality variables. However, on-line acquisition of such data may involve difficulties due to inadequacy o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64f381924fa4004b324d8dc026857530
https://doi.org/10.1016/j.jprocont.2013.05.007
https://doi.org/10.1016/j.jprocont.2013.05.007
Autor:
Enbo Feng, Elom Ayih Domlan, Yu Miao, Shima Khatibisepehr, Aris Espejo, Marziyeh Keshavarz, Swanand Khare, Xinguang Shao, Fangwei Xu, Biao Huang, Yu Zhao, Elham Naghoosi, Ramesh Kadali
Publikováno v:
The Canadian Journal of Chemical Engineering. 91:1416-1426
Oil sands development is both a costly and technically complex business with potential concerns in land use, water consumption and greenhouse gas emissions. Therefore, it is of practical interest to further investigate novel techniques to improve pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::393a0d1a721d30f2b8ef3e56f7e76729
https://doi.org/10.1002/cjce.21833
https://doi.org/10.1002/cjce.21833
Development and industrial application of soft sensors with on-line Bayesian model updating strategy
Publikováno v:
Journal of Process Control. 23:317-325
This paper deals with the issues associated with the development of data-driven models as well as model update strategy for soft sensor applications. A practical yet effective solution is proposed. Key process variables that are difficult to measure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77cf8aa1e5bb49fd293839a93d663dbc
https://doi.org/10.1016/j.jprocont.2012.12.008
https://doi.org/10.1016/j.jprocont.2012.12.008
Publikováno v:
Journal of Process Control. 22:1913-1929
In the context of process industries, online monitoring of quality variables is often restricted by inadequacy of measurement techniques or low reliability of measuring devices. Therefore, there has been a growing interest in the development of infer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c25b8dc7c27c5d6ddbb2854e88edcf51
https://doi.org/10.1016/j.jprocont.2012.09.006
https://doi.org/10.1016/j.jprocont.2012.09.006
Autor:
Biao Huang, Shima Khatibisepehr
Publikováno v:
AIChE Journal. 59:845-859
In the context of process industries, outlying observations mostly represent a large random error resulting from irregular process disturbances, instrument failures, or transmission problems. Statistical analysis of process data contaminated with out
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab738142c5ddfe29b124fe07a37aedfc
https://doi.org/10.1002/aic.13887
https://doi.org/10.1002/aic.13887