Experiments with the use of a rule-based self-organising controller for robotics applications
Fuzzy Sets and Systems - Fuzzy Control
Extracting compact fuzzy rules based on adaptive data approximation using B-splines
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent information systems and applications
Automatic generation of fuzzy rule-based models from data by genetic algorithms
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
International Journal of Approximate Reasoning
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Induction of multiple fuzzy decision trees based on rough set technique
Information Sciences: an International Journal
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Probabilistic fuzzy systems in value-at-risk estimation
International Journal of Intelligent Systems in Accounting and Finance Management - Risk Analysis in Complex Systems: Intelligent Systems in Finance
Least squares estimation of a linear regression model with LR fuzzy response
Computational Statistics & Data Analysis
Improving generalization of fuzzy IF-THEN rules by maximizing fuzzy entropy
IEEE Transactions on Fuzzy Systems
Scalability in fuzzy rule-based learning
Information Sciences: an International Journal
Information Sciences: an International Journal
A probabilistic fuzzy approach to modeling nonlinear systems
Neurocomputing
Learning interpretable fuzzy inference systems with FisPro
Information Sciences: an International Journal
A survey-based type-2 fuzzy logic system for energy management in hybrid electrical vehicles
Information Sciences: an International Journal
Approximation accuracy analysis of fuzzy systems as function approximators
IEEE Transactions on Fuzzy Systems
A new approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Approximation accuracy of some neuro-fuzzy approaches
IEEE Transactions on Fuzzy Systems
GA-fuzzy modeling and classification: complexity and performance
IEEE Transactions on Fuzzy Systems
Maximum Ambiguity-Based Sample Selection in Fuzzy Decision Tree Induction
IEEE Transactions on Knowledge and Data Engineering
Learning and tuning fuzzy logic controllers through reinforcements
IEEE Transactions on Neural Networks
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
Hi-index | 0.07 |
This study considers probabilistic fuzzy systems constructed using Mamdani probabilistic fuzzy rules. As a generalisation of deterministic fuzzy systems, Mamdani probabilistic fuzzy systems better model practical complex systems involving uncertainty because they combine the interpretability of fuzzy systems with the statistical properties of probabilistic systems. Using probabilistic fuzzy rules, both probabilistic uncertainty and linguistic ambiguity are handled simultaneously with a single framework. Considering that the information available often consists of a training set of input-output data pairs, a general method for generating Mamdani probabilistic fuzzy rule bases from numerical data pairs is presented. A fuzzy reasoning method is used on the generated probabilistic fuzzy rule base to derive a map leading from the input space to the output space, and a probabilistic fuzzy system is constructed. We use this probabilistic fuzzy modelling method for nonlinear regression analysis. The effectiveness of the proposed method is demonstrated by a comparison with similar regression techniques.