| Title |
Design of a Hierarchically Structured Gas Identification System Using Fuzzy Sets and Rough Sets |
| Authors |
방영근(Young-Keun Bang) ; 이철희(Chul-Heui Lee) |
| DOI |
http://doi.org/10.5370/KIEE.2018.67.3.419 |
| Keywords |
Gas identification ; Hybrid genetic algorithm ; Hierarchical structure ; TSK fuzzy rules ; Rough set |
| Abstract |
An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases. |