RSPOP: Rough Set–Based Pseudo Outer-Product Fuzzy Rule Identification Algorithm
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Publication:5696488
DOI10.1162/0899766052530857zbMath1092.68637OpenAlexW2133085637WikidataQ51576453 ScholiaQ51576453MaRDI QIDQ5696488
Publication date: 18 October 2005
Published in: Neural Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1162/0899766052530857
Learning and adaptive systems in artificial intelligence (68T05) Fuzzy control/observation systems (93C42) Knowledge representation (68T30)
Related Items (2)
A Novel Generic Hebbian Ordering-Based Fuzzy Rule Base Reduction Approach to Mamdani Neuro-Fuzzy System ⋮ RSPOP
Cites Work
- POPFNN: A pseudo outer-product based fuzzy neural network
- Structure identification of fuzzy model
- On rule pruning using fuzzy neural networks
- Construction of fuzzy inference rules by NDF and NDFL
- The concept of a linguistic variable and its application to approximate reasoning. I
- The concept of a linguistic variable and its application to approximate reasoning. II
- The concept of a linguistic variable and its application to approximate reasoning. III
- Sugeno controllers with a bounded number of rules are nowhere dense
- Interpolation of fuzzy if-then rules by neural networks
- A survey on universal approximation and its limits in soft computing techniques.
- A rough-fuzzy approach for generating classification rules
- A review and comparison of six reasoning methods
- Fuzzy identification of systems and its applications to modeling and control
- An experiment in linguistic synthesis with a fuzzy logic controller
- Rough set methods in feature selection and recognition
- Antiforgery: a novel pseudo-outer product based fuzzy neural network driven signature verification system
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