This paper proposes a self-learning kernel regression model. It learns a specific kernel space from input and output data, simultaneously considering the�...
Abstract—The traditional kernel data-driven regression methods would not guarantee a good prediction performance as the kernel space of the traditional�...
The modified spun fiber is used for sensitive fiber coil of sensor. The sensor has accuracy of 0.5% at temperature range from -40 degrees C to 60 degrees C�...
Sep 12, 2024 � We propose an interpretable industrial soft sensor based on Graph Sampling and Aggregation Temporal Convolutional Network Improved by Multi-head Self-Attention�...
May 2, 2022 � Recently, soft sensor models based on deep-learning techniques have been successfully applied to complex industrial processes with nonlinear and�...
Chihang Wei, Junghui Chen, Zhihuan Song, Chun-I Chen: Soft sensors of nonlinear industrial processes based on self-learning kernel regression model.
To depict nonlinear relationships between variables, nonlinear models in the machine learning community were further involved in soft sensors, represented by�...
Development of Self-Learning Kernel Regression Models for Virtual ...
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This paper aims to develop a high-accuracy virtual sensor based on the self-learning kernel regression (SLKR) model, which simultaneously constructs the�...
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Aug 10, 2014 � In this paper, a just-in-time learning (JITL) based locally weighted kernel principal component regression (LWKPCR) is proposed to solve the nonlinear and time�...
Jun 4, 2024 � This paper proposes an AKBLS algorithm that reduces uncertainty, eliminates redundant features, and improves prediction accuracy by projecting feature nodes�...