Fuzzy Broad Neuroevolution Networks via Multiobjective Evolutionary Algorithms: Balancing Structural Simplification and Performance

Dynamic fuzzy broad learning system (DFBLS) is a fuzzy neural network based on the TSK fuzzy system and broad learning (BL). DFBLS possesses excellent model interpretability and efficient predictive performance. However, due to the phenomenon of rule explosion and the redundancy of network nodes, ba...

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Vydáno v:	IEEE transactions on instrumentation and measurement Ročník 74; s. 1 - 10
Hlavní autoři:	Zhao, Huimin, Wu, Yandong, Deng, Wu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Balancing Complexity-accuracy trade-off Computational modeling Datasets Evolutionary algorithms Evolutionary computation Feature extraction fuzzy broad networks Fuzzy logic fuzzy rule (FR)-based classification systems Fuzzy sets Genetic algorithms Learning systems Linear programming Machine learning multiobjective evolutionary network framework Multiple objective analysis Neural networks Optimization Predictions Predictive models Redundancy Training
ISSN:	0018-9456, 1557-9662
On-line přístup:	Získat plný text
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