A new type of recurrent fuzzy neural network for modeling dynamic systems

Knowledge-Based Systems

Volumn 14, Issue 5-6, 2001, Pages 243-251

  Zhou, Shang Ming ^a   Xu, Li Da ^b  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b WRIGHT STATE UNIVERSITY   (United States)

Author keywords

Dynamic system; Fuzzy control; Fuzzy modeling; Recurrent neural network

Indexed keywords

ALGORITHMS; FUZZY CONTROL; FUZZY SETS; MATHEMATICAL MODELS;

FUZZY DYNAMICAL SYSTEMS (FDS); RECURRENT FUZZY NEURAL NETWORKS (RFNN);

RECURRENT NEURAL NETWORKS;

EID: 0035422763     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0950-7051(01)00102-2     Document Type: Article

References (13)

1. Recurrent fuzzy logic in speech recognition
2. Dynamic neural networks that ensure exponential identification error convergence
3. Formal approach to fuzzy modeling
4. Real-time fuzzy adaptive control
5. Fuzzy identification of systems and its applications to modelling and control
6. Stability analysis and design of fuzzy control systems
7. An adaptive control method for time-varying systems
8. Maximizing long-term gas industry profits in two minutes in Lotus using neural networks method
9. Fuzzy Sets
10. Use of inverse for the error-correcting BAM and learning
11. Dynamic neural network and image sequences with applications to building the model for complex productions
12. Combining dynamic neural network and image sequences in a model for complex industrial processes