Multiscale dynamic feature learning for quality prediction based on hierarchical sequential generative network
In industrial processes, long short-term memory (LSTM) is usually used for temporal
dynamic modeling of soft sensor. The process data usually have various temporal …
dynamic modeling of soft sensor. The process data usually have various temporal …
Soft sensor development for the key variables of complex chemical processes using a novel robust bagging nonlinear model integrating improved extreme learning …
YL He, ZQ Geng, QX Zhu - Chemometrics and Intelligent Laboratory …, 2016 - Elsevier
Some key variables in the complex chemical processes are very difficult to measure due to
the nonlinearity, the disturbances, and the technological limitations. In order to accurately …
the nonlinearity, the disturbances, and the technological limitations. In order to accurately …
Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm
An optimized design of a fuzzy logic system can be regarded as setting of different
parameters of the system automatically. For a single parameter, there may exist multiple …
parameters of the system automatically. For a single parameter, there may exist multiple …