Online prediction of Mooney viscosity in industrial rubber mixing process via adaptive kernel learning method

2009 ◽  
Author(s):  
Diancai Yang ◽  
Yi Liu ◽  
Yugang Fan ◽  
Haiqing Wang
Keyword(s):  
Kernel Learning ◽  
Learning Method ◽  
Mixing Process ◽  
Adaptive Kernel ◽  
Industrial Rubber ◽  
Mooney Viscosity ◽  
Online Prediction

scholarly journals Ensemble Just-In-Time Learning-Based Soft Sensor for Mooney Viscosity Prediction in an Industrial Rubber Mixing Process

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Huaiping Jin ◽  
Jiangang Li ◽  
Meng Wang ◽  
Bin Qian ◽  
Biao Yang ◽  
...  
Keyword(s):  
Gaussian Process Regression ◽  
Soft Sensor ◽  
Viscosity Measurement ◽  
Finite Mixture ◽  
Just In Time ◽  
Mixing Process ◽  
Industrial Rubber ◽  
Viscosity Prediction ◽  
Mooney Viscosity ◽  
Input Variables

The lack of online sensors for Mooney viscosity measurement has posed significant challenges for enabling efficient monitoring, control, and optimization of industrial rubber mixing process. To obtain real-time and accurate estimations of Mooney viscosity, a novel soft sensor method, referred to as multimodal perturbation- (MP-) based ensemble just-in-time learning Gaussian process regression (MP-EJITGPR), is proposed by exploiting ensemble JIT learning. This method employs perturbations on similarity measure and input variables for generating the diversity of JIT learners. Furthermore, a set of accurate and diverse JIT learners are built through an evolutionary multiobjective optimization by balancing the accuracy and diversity objectives explicitly. Moreover, all base JIT learners are combined adaptively using a finite mixture mechanism. The proposed method is applied to an industrial rubber mixing process for Mooney viscosity prediction, and the experimental results demonstrate its effectiveness and superiority over traditional soft sensor methods.

Ensemble Correntropy-Based Mooney Viscosity Prediction Model for an Industrial Rubber Mixing Process

2016 ◽  
Vol 39 (10) ◽  
pp. 1804-1812 ◽  
Author(s):  
Yi Liu ◽  
Yu Fan ◽  
Lichun Zhou ◽  
Fujiang Jin ◽  
Zengliang Gao
Keyword(s):  
Prediction Model ◽  
Mixing Process ◽  
Industrial Rubber ◽  
Viscosity Prediction ◽  
Mooney Viscosity

Deep kernel learning method for SAR image target recognition

2017 ◽  
Vol 88 (10) ◽  
pp. 104706 ◽  
Author(s):  
Xiuyuan Chen ◽  
Xiyuan Peng ◽  
Ran Duan ◽  
Junbao Li
Keyword(s):  
Target Recognition ◽  
Kernel Learning ◽  
Sar Image ◽  
Learning Method
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