The role of fuzzy logic in the management of uncertainty in expert systems
Fuzzy Sets and Systems
| Hi-index | 0.00 |
This paper presents information processing and representation as an intelligent regulation system. The paper illustrates advanced numerical method in an intelligent control system. The fuzzy membership function allow preserving more quantitative information in the reasoning process, where as the class values can still be used to process the available information in a qualitative fashion. The qualitative analysis allows to generate quickly a rough qualitative response. The fuzzy membership functions can then be used to smoothly interpolate between the qualitative class values to obtain a quasi continuous respons spectrum. A contribution of this paper is advanced information regulation in improving control quality. The fuzzy controller adapts a system which varies slowly over time for uncertainty disturbance. Transfer and transformation facts and rules for problem solving were described. Decision making mechanism was implemented.