Abstract:
In this paper, a probabilistic fuzzy logic system (PFLS) is discussed for modeling the stochastic and imprecise information. The PFLS uses a 3-dimensional probabilistic f...Show MoreMetadata
Abstract:
In this paper, a probabilistic fuzzy logic system (PFLS) is discussed for modeling the stochastic and imprecise information. The PFLS uses a 3-dimensional probabilistic fuzzy set to capture the imprecise stochastic information. A unique 3-dimensional probabilistic fuzzy logic is designed to perform rule inference under such imprecise and stochastic environment. When the PFLS and neural networks are integrated in a unified framework, it can further adapt to time varying dynamics so as to improve its modeling performance. The paper briefly reviews this unique development and potential power of probabilistic fuzzy logic system.
Published in: 2009 IEEE International Conference on Fuzzy Systems
Date of Conference: 20-24 August 2009
Date Added to IEEE Xplore: 02 October 2009
ISBN Information:
Print ISSN: 1098-7584
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- IEEE Keywords
- Index Terms
- Fuzzy Logic ,
- Probable Reason ,
- Fuzzy System ,
- Imprecise Information ,
- Probabilistic System ,
- Stochastic Information ,
- Neural Network ,
- Fuzzy Set ,
- Stochastic Environment ,
- Time-varying Dynamics ,
- Bayesian Inference ,
- Probability Density Function ,
- Rule-based ,
- Nonlinear Systems ,
- Random Noise ,
- Stochastic Model ,
- Global Optimization ,
- Control Applications ,
- Stochastic Nature ,
- Statistical Analysis Methods ,
- Stochastic Uncertainty ,
- Inference System ,
- Stochastic Character ,
- Probabilistic Process ,
- Fuzzy Information ,
- Evidence Theory ,
- Fuzzy Neural Network ,
- Fuzzy Membership Functions ,
- Probabilistic Inference ,
- Universal Approximation
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Fuzzy Logic ,
- Probable Reason ,
- Fuzzy System ,
- Imprecise Information ,
- Probabilistic System ,
- Stochastic Information ,
- Neural Network ,
- Fuzzy Set ,
- Stochastic Environment ,
- Time-varying Dynamics ,
- Bayesian Inference ,
- Probability Density Function ,
- Rule-based ,
- Nonlinear Systems ,
- Random Noise ,
- Stochastic Model ,
- Global Optimization ,
- Control Applications ,
- Stochastic Nature ,
- Statistical Analysis Methods ,
- Stochastic Uncertainty ,
- Inference System ,
- Stochastic Character ,
- Probabilistic Process ,
- Fuzzy Information ,
- Evidence Theory ,
- Fuzzy Neural Network ,
- Fuzzy Membership Functions ,
- Probabilistic Inference ,
- Universal Approximation