Hybridizing Hierarchical and Weighted Linguistic Rules
Proceedings of the 2002 ACM symposium on Applied computing
Improving Simple Linguistic Fuzzy Models by Means of the Weighted COR Methodology
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
A Study on the Evolutionary Adaptive Defuzzification Methods in Fuzzy Modeling
International Journal of Hybrid Intelligent Systems
International Journal of Approximate Reasoning
A case study for learning behaviors in mobile robotics by evolutionary fuzzy systems
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
International Journal of Approximate Reasoning
Interpretability, interpolation and rule weights in linguistic fuzzy modeling
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
On employing fuzzy modeling algorithms for the valuation of residential premises
Information Sciences: an International Journal
Navigating interpretability issues in evolving fuzzy systems
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Adaptability, interpretability and rule weights in fuzzy rule-based systems
Information Sciences: an International Journal
| Hi-index | 0.00 |
It may not always be possible for an expert to provide a set of completely consistent rules. Even if the rules are consistent, all rules may not have equal importance to control the system. Moreover, for a fuzzy controller, the rule-base is usually tuned through modification of membership functions. Effect of changing a membership function is global in the sense that it influences all rules that involve the membership function. Here we propose a very effective extension of the conventional fuzzy reasoning system with incorporation of an importance factor for each rule. This factor allows tuning of the system at the rule level. Of course, one can still tune the membership functions. It enables the system to cope with incorrect and/or incompatible rules and thereby enhances the robustness, flexibility and system modeling capability. The proposed model is quite general and can be used in different applications including control. In the present investigation, we demonstrate with extensive simulation how for a control application inconsistent rules can be dealt with.