Fuzzy system based on two-step cascade genetic optimization strategy for tobacco tar prediction
- There are many challenges in accurately measuring cigarette tar constituents. These include the need for standardized smoke generation methods related to unstable mixtures. In this research were developed algorithms using fusion of artificial intelligence methods to predict tar concentration. Outputs of development are three fuzzy structures optimized with genetic algorithms resulting in genetic algorithm (GA)-FUZZY, GA-adaptive neuro fuzzy inference system (ANFIS), GA-GA-FUZZY algorithms. Proposed algorithms are used for the tar prediction in the cigarette production process. The results of prediction are compared with gas chromatograph (high-performance liquid chromatography (HPLC)) readings.
Download full text files
Additional Services
| Author: | Muamer Kafadar, Zikrija Avdagic, Lejla Begic Fazlic |
|---|---|
| URN: | urn:nbn:de:hbz:tr5-1396 |
| DOI: | https://doi.org/10.2991/ijcis.d.191122.001 |
| Parent Title (English): | International Journal of Computational Intelligence Systems |
| Publisher: | Atlantis Press |
| Document Type: | Article (specialist journals) |
| Language: | English |
| Date of OPUS upload: | 2022/09/15 |
| Date of first Publication: | 2019/12/03 |
| Publishing University: | Hochschule Trier |
| Release Date: | 2022/09/15 |
| Tag: | GA-ANFIS; GA-FUZZY; GA-GA-FUZZY; adaptive neuro fuzzy system; fuzzy logic; genetic algorithm; tar |
| GND Keyword: | Fuzzy-Logik; Neuro-Fuzzy-System; Genetischer Algorithmus; Zigarettenrauch; Teer |
| Volume: | 12 |
| Issue: | 2 |
| Page Number: | 15 |
| First Page: | 1497 |
| Last Page: | 1511 |
| Departments: | FB Umweltplanung/-technik (UCB) |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme |
| 5 Naturwissenschaften und Mathematik / 54 Chemie | |
| Licence (German): |  Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International |
