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research-article

An Efficient Self-Organizing Deep Fuzzy Neural Network for Nonlinear System Modeling

Authors:

Junfei QiaoAuthors Info & Claims

IEEE Transactions on Fuzzy Systems, Volume 30, Issue 7

Pages 2170 - 2182

https://doi.org/10.1109/TFUZZ.2021.3077396

Published: 01 July 2022 Publication History

Abstract

A fuzzy neural network (FNN) is an effective learning system that combines neural network and fuzzy logic, which has achieved great success in nonlinear system modeling. However, when the input is practical complex data with external disturbance, the existing FNN cannot extract effective input features sufficiently, leading to unsatisfactory performances in learning speed and accuracy. It also fails to achieve a better generalization capability because of its fixed structure size (the number of rule neurons). In this article, an efficient self-organizing FNN (SOFNN) with incremental deep pretraining (IDPT), called IDPT-SOFNN, is developed to overcome these shortcomings. First, IDPT is designed to extract effective features and consider them as the input of the SOFNN. Different from the existing pretraining, the self-growing structure of IDPT improves pretraining efficiency with a more compact structure. Second, the SOFNN can dynamically add and delete neurons according to the current error and error-reduction rate. In this case, it can obtain better modeling performance with a more compact structure as well. Third, as a novel hybrid model with the cascade dual-self-organizing algorithm, the IDPT-SOFNN combines the advantage of IDPT and SOFNN. Moreover, the convergence and stability are analyzed. Finally, simulation studies and comparisons demonstrate that the proposed IDPT-SOFNN has better performances than its peers in learning speed, accuracy, and generalization capability.

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Cited By

Ying NLi HZhang ZZhou YChen HYang M(2025)ViTDFNN: A Vision Transformer Enabled Deep Fuzzy Neural Network for Detecting Sleep Apnea-Hypopnea Syndrome in the Internet of Medical ThingsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.338809133:1(82-93)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3388091
Lu JMa GZhang G(2024)Fuzzy Machine Learning: A Comprehensive Framework and Systematic ReviewIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.338742932:7(3861-3878)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3387429
Wang GChen HHan HBi JQiao JTirkolaee E(2024)Predicting Water Quality With Nonstationarity: Event-Triggered Deep Fuzzy Neural NetworkIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.335491932:5(2690-2699)Online publication date: 29-Jan-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3354919
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Index Terms

An Efficient Self-Organizing Deep Fuzzy Neural Network for Nonlinear System Modeling
1. Computing methodologies
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Machine learning theory

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Fuzzy Systems

IEEE Transactions on Fuzzy Systems Volume 30, Issue 7

July 2022

641 pages

ISSN:1063-6706

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1063-6706 © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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IEEE Press

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Published: 01 July 2022

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Cited By

Ying NLi HZhang ZZhou YChen HYang M(2025)ViTDFNN: A Vision Transformer Enabled Deep Fuzzy Neural Network for Detecting Sleep Apnea-Hypopnea Syndrome in the Internet of Medical ThingsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.338809133:1(82-93)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3388091
Lu JMa GZhang G(2024)Fuzzy Machine Learning: A Comprehensive Framework and Systematic ReviewIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.338742932:7(3861-3878)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3387429
Wang GChen HHan HBi JQiao JTirkolaee E(2024)Predicting Water Quality With Nonstationarity: Event-Triggered Deep Fuzzy Neural NetworkIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.335491932:5(2690-2699)Online publication date: 29-Jan-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3354919
Li KQiao JWang D(2024)Fuzzy Stochastic Configuration Networks for Nonlinear System ModelingIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2023.331536832:3(948-957)Online publication date: 1-Mar-2024
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Han HFeng CSun HQiao J(2024)Predictor-Based Self-Organizing Control for Unknown Nonlinear Dynamical SystemsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2023.329833332:2(524-535)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2023.3298333
Salimi-Badr A(2024)A data-driven implicit deep adaptive neuro-fuzzy inference system capable of manifold learning for function approximationApplied Soft Computing10.1016/j.asoc.2024.111458155:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.asoc.2024.111458
Ouifak HIdri A(2023)Application of neuro-fuzzy ensembles across domainsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106582124:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.106582
Zhou HLi YZhang QXu HSu Y(2022)Soft-sensing of effluent total phosphorus using adaptive recurrent fuzzy neural network with Gustafson-Kessel clusteringExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.117589203:COnline publication date: 1-Oct-2022
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Muthusamy DSathyamoorthy S(2022)Deep belief network for solving the image quality assessment in full reference and no reference modelNeural Computing and Applications10.1007/s00521-022-07649-934:24(21809-21833)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s00521-022-07649-9

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