Fourier-based type-2 fuzzy neural network: Simple and effective for high dimensional problems

A Mohammadzadeh, C Zhang, KA Alattas… - Neurocomputing, 2023 - Elsevier
The main contribution of this study is to introduce a simple and effective deep learning
Fourier-based type-2 fuzzy neural network for high-dimensional problems. The rules are …

[HTML][HTML] A Review of AI-Driven Control Strategies in the Activated Sludge Process with Emphasis on Aeration Control

C Monday, MS Zaghloul, D Krishnamurthy, G Achari - Water, 2024 - mdpi.com
Recent concern over energy use in wastewater treatment plants (WWTPs) has spurred
research on enhancing efficiency and identifying energy-saving technologies. Treating one …

Dynamic submodular-based learning strategy in imbalanced drifting streams for real-time safety assessment in nonstationary environments

Z Liu, X He - IEEE Transactions on Neural Networks and …, 2023 - ieeexplore.ieee.org
The design of real-time safety assessment (RTSA) approaches in nonstationary
environments is meaningful to reduce the possibility of significant losses. However, several …

A real-time adaptive fault diagnosis scheme for dynamic systems with performance degradation

X He, C Li, Z Liu - IEEE Transactions on Reliability, 2023 - ieeexplore.ieee.org
The degradation of a system's performance poses a significant challenge to the effective
application of fault diagnosis methods for dynamic systems. Consequently, the underlying …

IT2CFNN: An interval type-2 correlation-aware fuzzy neural network to construct non-separable fuzzy rules with uncertain and adaptive shapes for nonlinear function …

A Salimi-Badr - Applied Soft Computing, 2022 - Elsevier
In this paper, a new interval type-2 fuzzy neural network able to construct non-separable
fuzzy rules with various shapes is introduced for function approximation problems. To reflect …

Efficient fault monitoring in wastewater treatment processes with time stacked broad learning network

C Peng, X Ying, M FanChao - Expert Systems with Applications, 2023 - Elsevier
Process monitoring models play an increasingly indispensable role in promptly
differentiating faults within the wastewater treatment process to maintain a safe state. The …

Adaptive Incremental Broad Learning System Based on Interval Type-2 Fuzzy Set with Automatic Determination of Hyperparameters

H Wu, W Lin, Y Chen, F Shi, W Shen… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
The fuzzy broad learning system (FBLS) has received increasing attention due to its ability to
quickly train from broad learning systems (BLS) and interpretability with fuzzy inference …

Fault detection in wastewater treatment process using broad slow feature neural network with incremental learning ability

P Chang, Y Xu, F Meng, W ** a fault detection model for the wastewater treatment process that combines
satisfactory accuracy with comparatively low time overhead remains an exceedingly …

Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel

A Rospawan, CC Tsai, CC Hung - International Journal of Fuzzy Systems, 2024 - Springer
This paper presents a novel intelligent control method using an output recurrent fuzzy broad
learning system (ORFBLS) for robust setpoint tracking control of nonlinear digital multi-input …

Broad learning system based ensemble deep model

C Zhang, S Ding, L Guo, J Zhang - Soft Computing, 2022 - Springer
Broad learning system (BLS) demonstrates a novel structure of neural networks based on
random vector functional link network (RVFL), which has a faster modeling speed, better …