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Titlebook: Data-Driven Fault Detection and Reasoning for Industrial Monitoring; Jing Wang,Jinglin Zhou,Xiaolu Chen Book‘‘‘‘‘‘‘‘ 2022 The Editor(s) (i

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樓主: concord
31#
發(fā)表于 2025-3-26 23:00:09 | 只看該作者
Kernel Fisher Envelope Surface for Pattern Recognition,d of a batch. Therefore, the complete batch trajectory must be estimated real time, or alternatively only the measured values at the current moment are used for online diagnosis. Moreover, the above approaches do not consider the problem of inconsistent production cycles.
32#
發(fā)表于 2025-3-27 01:21:09 | 只看該作者
Fault Identification Based on Local Feature Correlation,ough appropriate kernel functions so as to achieve the goal of linear separability in the new space. However, the space projection from the low dimension to the high dimension is contradictory to the actual requirement of dimensionality reduction of the data. So kernel-based method inevitably increases the complexity of data processing.
33#
發(fā)表于 2025-3-27 06:03:57 | 只看該作者
34#
發(fā)表于 2025-3-27 12:10:29 | 只看該作者
35#
發(fā)表于 2025-3-27 14:13:15 | 只看該作者
Reversible Pebble Game on Treesm shutdowns and thus possibly huge economic losses. Maximum correlation was extracted between quality variables and process variables by partial least squares analysis (PLS) (Kruger et?al. .; Song et?al. .; Li et?al. .; Hu et?al. .; Zhang et?al. .).
36#
發(fā)表于 2025-3-27 21:35:55 | 只看該作者
Bin Packing Game with an Interest Matrixainty part, just as the nonlinearity can be used to represent the uncertainty of a system (Wang et?al. .). So this chapter also focuses on how to deal with the nonlinearity in PLS series method, but starts from an different view, i.e., robust PLS. Here the system nonlinearity is considered as uncertainty and a new robust .-PLS is proposed.
37#
發(fā)表于 2025-3-27 22:52:43 | 只看該作者
Marc Hellmuth,Guillaume E. Scholzk, but its parameter learning method can only handle the discrete variables. This chapter aims at the probabilistic graphical model directly for the continuous process variables, which avoids the assumption of discrete or Gaussian distributions.
38#
發(fā)表于 2025-3-28 03:39:06 | 只看該作者
Book‘‘‘‘‘‘‘‘ 2022 who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications.?.This is an open access book..
39#
發(fā)表于 2025-3-28 07:05:54 | 只看該作者
Data-Driven Fault Detection and Reasoning for Industrial Monitoring
40#
發(fā)表于 2025-3-28 13:04:55 | 只看該作者
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