X-Fuzz: An Evolving and Interpretable Neuro-Fuzzy Learner for Data Streams
Author:
Affiliation:
1. Department of Computer Science, The University of New Orleans, New Orleans, LA, USA
2. Air Traffic Management Research Institute (ATMRI), Nanyang Technological University, Singapore
Funder
National Research Foundation, Singapore
Civil Aviation Authority of Singapore
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9078688/10635096/10432928.pdf?arnumber=10432928
Reference51 articles.
1. Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams
2. On Paradigm of Industrial Big Data Analytics: From Evolution to Revolution
3. Two-Stage Sparse Representation Clustering for Dynamic Data Streams
4. Data driven modelling based on Recurrent Interval-Valued Metacognitive Scaffolding Fuzzy Neural Network
5. Adaptive Learning from Evolving Data Streams
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Systematic Review of Forecasting Models Using Evolving Fuzzy Systems;Computation;2024-08-08
2. A Dynamic Evolving Fuzzy System for Streaming Data Prediction;IEEE Transactions on Fuzzy Systems;2024-08
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