Soft-sensing of effluent total phosphorus using adaptive recurrent fuzzy neural network with Gustafson-Kessel clustering
H Zhou, Y Li, Q Zhang, H Xu, Y Su - Expert Systems with Applications, 2022 - Elsevier
To address the issue of soft-sensing of effluent total phosphorus in wastewater treatment
processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural …
processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural …
Research on supply chain financial risk assessment based on blockchain and fuzzy neural networks
Y Wang - Wireless Communications and Mobile Computing, 2021 - Wiley Online Library
With the development of supply chain finance, the credit risk of small‐and medium‐sized
financing enterprises from the perspective of supply chain finance has arisen. Risk …
financing enterprises from the perspective of supply chain finance has arisen. Risk …
One-dimensional convolutional neural network (1D-CNN) image reconstruction for electrical impedance tomography
X Li, R Lu, Q Wang, J Wang, X Duan, Y Sun… - Review of scientific …, 2020 - pubs.aip.org
In recent years, due to the strong autonomous learning ability of neural network algorithms,
they have been applied for electrical impedance tomography (EIT). Although their imaging …
they have been applied for electrical impedance tomography (EIT). Although their imaging …
Optimization of aluminum fluoride addition in aluminum electrolysis process based on pruned sparse fuzzy neural network
The aluminum fluoride (AF) addition in aluminum electrolysis process (AEP) can directly
influence the current efficiency, energy consumption, and stability of the process. This paper …
influence the current efficiency, energy consumption, and stability of the process. This paper …
Joint label-specific features and label correlation for multi-label learning with missing label
Z Cheng, Z Zeng - Applied Intelligence, 2020 - Springer
Existing multi-label learning classification algorithms ignore that class labels may be
determined by some features in the original feature space. And only a partial label of each …
determined by some features in the original feature space. And only a partial label of each …
Efficient quality variable prediction of industrial process via fuzzy neural network with lightweight structure
Quality Variables of industrial processes generally require to be obtained as fast as
possible. In this paper, a correlation-wise self-organizing fuzzy neural network (CwSFNN) for …
possible. In this paper, a correlation-wise self-organizing fuzzy neural network (CwSFNN) for …
E‐Commerce Enterprise Supply Chain Financing Risk Assessment Based on Linked Data Mining and Edge Computing
Q Qu, C Liu, X Bao - Mobile Information Systems, 2021 - Wiley Online Library
In recent years, the rapid development of information technology has affected the way the
world economy operates. The emergence of e‐commerce has greatly shortened the time …
world economy operates. The emergence of e‐commerce has greatly shortened the time …
Large-Scale and Knowledge-Based Dynamic Multiobjective Optimization for MSWI Process Using Adaptive Competitive Swarm Optimization
W Huang, H Ding, J Qiao - IEEE Transactions on Systems, Man …, 2023 - ieeexplore.ieee.org
Municipal solid waste incineration (MSWI) process is a complex industrial process with
strong nonlinearity. It is a challenge to build a model for the MSWI process and carry out the …
strong nonlinearity. It is a challenge to build a model for the MSWI process and carry out the …
Optimal deep learning control for modernized microgrids
SR Yan, W Guo, A Mohammadzadeh… - Applied Intelligence, 2023 - Springer
In this study, a new control approach is introduced for active/reactive power control in
modernized microgrids (MMGs). The dynamics of MMG are considered to be unknown and a …
modernized microgrids (MMGs). The dynamics of MMG are considered to be unknown and a …
An online self-organizing modular neural network for nonlinear system modeling
J Qiao, X Guo, W Li - Applied Soft Computing, 2020 - Elsevier
Modular neural network (MNN) has distinct advantage in many fields such as pattern
recognition and pattern recognition. However it is still a challenge to dynamically adjust the …
recognition and pattern recognition. However it is still a challenge to dynamically adjust the …