Abstract: Soft sensor are widely used to estimate process variables which are difficult to measure online in industrial process control.
Soft sensor are widely used to estimate process variables which are difficult to measure online in industrial process control. This paper proposes a new ...
A new soft sensor modeling method based on a deep learning method, which integrates denoising auto-encoders (DAE) with support vector regression (SVR) ...
Oct 10, 2024 · In this study, we have chosen nine parameters, including intrinsic acidity, free acidity, citric acid concentration, residual sugar ...
This paper proposes a new soft sensor modeling method based on a deep learning method, which integrates denoising auto-encoders (DAE) with support vector ...
This paper introduced the deep learning technique as a novel data-driven soft sensor modeling method.
Feb 15, 2020 · This paper presents a variational autoencoder-based just-in-time (JIT) learning framework for soft sensor modeling.
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Feb 7, 2020 · This paper proposes a semisupervised deep neural regression network with embedding manifold (SSE-DNN) for soft sensor modeling that integrates manifold ...
Jan 15, 2021 · A data-driven soft sensor modeling method based on deep neural network (DNN) is proposed in this paper. This method is suitable for large amount of data.
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Apr 11, 2022 · Here, a soft sensor is constructed for estimating the reactive power consumption value for every structural object, which is supplied along with ...