[HTML][HTML] Random vector functional link network: recent developments, applications, and future directions
Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …
classification, regression and clustering, etc. Generally, the back propagation (BP) based …
Data-driven soft sensors in blast furnace ironmaking: a survey
The blast furnace is a highly energy-intensive, highly polluting, and extremely complex
reactor in the ironmaking process. Soft sensors are a key technology for predicting molten …
reactor in the ironmaking process. Soft sensors are a key technology for predicting molten …
An unsupervised parameter learning model for RVFL neural network
With the direct input–output connections, a random vector functional link (RVFL) network is a
simple and effective learning algorithm for single-hidden layer feedforward neural networks …
simple and effective learning algorithm for single-hidden layer feedforward neural networks …
Data-driven robust M-LS-SVR-based NARX modeling for estimation and control of molten iron quality indices in blast furnace ironmaking
Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on
a reliable measurement of molten iron quality (MIQ) indices, which are not feasible using the …
a reliable measurement of molten iron quality (MIQ) indices, which are not feasible using the …
Robust stochastic configuration networks for industrial data modelling with student'st mixture distribution
A Yan, J Guo, D Wang - Information Sciences, 2022 - Elsevier
Data collected from industrial sites commonly contains outliers or noise that obey unknown
distributions, making it challenging to establish an accurate data-driven model. Therefore …
distributions, making it challenging to establish an accurate data-driven model. Therefore …
Data-driven nonlinear subspace modeling for prediction and control of molten iron quality indices in blast furnace ironmaking
Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-
chemical reactions, where multiphases and multifields interactions with long time delay …
chemical reactions, where multiphases and multifields interactions with long time delay …
Fuzzy nonlinear regression analysis using a random weight network
Modeling a fuzzy-in fuzzy-out system where both inputs and outputs are uncertain is of
practical and theoretical importance. Fuzzy nonlinear regression (FNR) is one of the …
practical and theoretical importance. Fuzzy nonlinear regression (FNR) is one of the …
Soft sensors based on adaptive stacked polymorphic model for silicon content prediction in ironmaking process
The silicon content of molten iron is a key index to reveal the thermal state in the blast
furnace (BF). To improve the quality of molten iron, it is important to obtain silicon content …
furnace (BF). To improve the quality of molten iron, it is important to obtain silicon content …
Blast furnace hot metal temperature and silicon content prediction using soft sensor based on fuzzy C-means and exogenous nonlinear autoregressive models
DOL Fontes, LGS Vasconcelos, RP Brito - Computers & Chemical …, 2020 - Elsevier
The temperature and silicon content of hot metal are essential parameters for the thermal
control of a blast furnace. However, the physical structure of the blast furnace prevents direct …
control of a blast furnace. However, the physical structure of the blast furnace prevents direct …
Multiobjective operation optimization of wastewater treatment process based on reinforcement self-learning and knowledge guidance
P Zhou, X Wang, T Chai - IEEE Transactions on Cybernetics, 2022 - ieeexplore.ieee.org
This article proposes a multiobjective operation optimization method based on
reinforcement self-learning and knowledge guidance for quality assurance and consumption …
reinforcement self-learning and knowledge guidance for quality assurance and consumption …