Just-in-time based soft sensors for process industries: A status report and recommendations
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 …
available easy-to-measure variables. These sensors are typically developed using either …
[HTML][HTML] A comprehensive overview of the applications of kernel functions and data-driven models in regression and classification tasks in the context of software …
Data-driven models can reduce the number of hardware sensors in a process plant by
acting as low-cost substitutes for hardware sensors. Since some data-driven models have …
acting as low-cost substitutes for hardware sensors. Since some data-driven models have …
Electrospun nanofiber membrane diameter prediction using a combined response surface methodology and machine learning approach
MN Pervez, WS Yeo, MMR Mishu, ME Talukder… - Scientific Reports, 2023 - nature.com
Despite the widespread interest in electrospinning technology, very few simulation studies
have been conducted. Thus, the current research produced a system for providing a …
have been conducted. Thus, the current research produced a system for providing a …
Prediction of the diameter of biodegradable electrospun nanofiber membranes: An integrated framework of taguchi design and machine learning
The ability to replicate electrospinning using a computer tool is of critical importance. Even
though electrospinning technology has received much attention, there haven't been many …
though electrospinning technology has received much attention, there haven't been many …
A comparative study between PCR, PLSR, and LW-PLS on the predictive performance at different data splitting ratios
TF Thien, WS Yeo - Chemical Engineering Communications, 2022 - Taylor & Francis
Principal component regression (PCR), partial least squares regression (PLSR), and locally
weighted partial least squares (LW-PLS) models are supervised learning methods in which …
weighted partial least squares (LW-PLS) models are supervised learning methods in which …
A comparative study of different kernel functions applied to LW-KPLS model for nonlinear processes
JCY Ngu, C Yeo - Biointerface Research in Applied Chemistry, 2022 - espace.curtin.edu.au
Soft sensors are inferential estimators when the employment of hardware sensors is
inapplicable, expensive, or difficult in industrial plant processes. Currently, a simple soft …
inapplicable, expensive, or difficult in industrial plant processes. Currently, a simple soft …
[HTML][HTML] Least squares support vector regression-based modeling of ammonia oxidation using immobilized nanoFeCu
The substantial release of ammonia (NH 3) into water streams results in eutrophication,
which is harmful to aquatic life. The effectiveness of immobilized iron‑copper bimetallic …
which is harmful to aquatic life. The effectiveness of immobilized iron‑copper bimetallic …
Predicting the whiteness index of cotton fabric with a least squares model
WS Yeo, WJ Lau - Cellulose, 2021 - Springer
The textile bleaching process that involves hot hydrogen peroxide (H 2 O 2) solution is
commonly practised in cotton fabric manufacture. The purpose of the bleaching process is to …
commonly practised in cotton fabric manufacture. The purpose of the bleaching process is to …
Adaptive soft sensor development for non-Gaussian and nonlinear processes
Just-in-time (JIT) adaptive soft sensors have been widely used in chemical processes
because they can deal with slow-varying processes, abrupt process changes, and outliers …
because they can deal with slow-varying processes, abrupt process changes, and outliers …
A review of just‐in‐time learning‐based soft sensor in industrial process
W Sheng, J Qian, Z Song… - The Canadian Journal of …, 2024 - Wiley Online Library
Data‐driven soft sensing approaches have been a hot research field for decades and are
increasingly used in industrial processes due to their advantages of easy implementation …
increasingly used in industrial processes due to their advantages of easy implementation …