Just-in-time based soft sensors for process industries: A status report and recommendations

WS Yeo, A Saptoro, P Kumar, M Kano - Journal of Process Control, 2023 - Elsevier
Soft sensors are mathematical models employed to estimate hard-to-measure variables from
available easy-to-measure variables. These sensors are typically developed using either …

Gaussian mixture continuously adaptive regression for multimode processes soft sensing under time-varying virtual drift

X Zhang, C Song, J Zhao, D **-**/publication/265604193_Adaptive_soft_sensor_modeling_framework_based_on_just-in-time_learning_and_kernel_partial_least_squares_regression_for_nonlinear_multiphase_batch_processes/links/5cf0042fa6fdcc8475f89f85/Adaptive-soft-sensor-modeling-framework-based-on-just-in-time-learning-and-kernel-partial-least-squares-regression-for-nonlinear-multiphase-batch-processes.pdf" data-clk="hl=pl&sa=T&oi=gga&ct=gga&cd=5&d=1498197127385411323&ei=q-GtZ_qyC-ehieoP4b3H4A0" data-clk-atid="-25RfVmqyhQJ" target="_blank">[PDF] researchgate.net

Adaptive soft sensor modeling framework based on just-in-time learning and kernel partial least squares regression for nonlinear multiphase batch processes

H **, X Chen, J Yang, L Wu - Computers & Chemical Engineering, 2014 - Elsevier
Batch processes are characterized by inherent nonlinearity, multiple phases and time-
varying behavior that pose great challenges for accurate state estimation. A multiphase just …

Adaptive virtual metrology design for semiconductor dry etching process through locally weighted partial least squares

T Hirai, M Kano - IEEE Transactions on Semiconductor …, 2015 - ieeexplore.ieee.org
In semiconductor manufacturing processes, virtual metrology (VM) has been investigated as
a promising tool to predict important characteristics of products. Although partial least …

Multi‐similarity measurement driven ensemble just‐in‐time learning for soft sensing of industrial processes

X Yuan, J Zhou, Y Wang, C Yang - Journal of Chemometrics, 2018 - Wiley Online Library
Just‐in‐time learning (JITL) technique has been widely used for adaptive soft sensing of
nonlinear processes. It builds online local model with the most relevant samples from …

Multi-model adaptive soft sensor modeling method using local learning and online support vector regression for nonlinear time-variant batch processes

H **, X Chen, J Yang, H Zhang, L Wang… - Chemical Engineering …, 2015 - Elsevier
Batch processes are often characterized by inherent nonlinearity, multiplicity of operating
phases, and batch-to-batch variations, which poses great challenges for accurate and …

[HTML][HTML] Covariance-based locally weighted partial least squares for high-performance adaptive modeling

K Hazama, M Kano - Chemometrics and Intelligent Laboratory Systems, 2015 - Elsevier
Locally weighted partial least squares (LW-PLS) is one of Just-in-Time (JIT) modeling
methods; PLS is used to build a local linear regression model every time when output …