Open Access
Dr. Yogeesh N
Dr. Lingaraju
Chetana. R
Dr. Vasanthakumari T N
Dr. P. William
- Assistant Professor , Department of Mathematics, Government First Grade College, Tumkur Karnataka India
- Associate Professor Department of Physics Government First Grade College, Tumkur Karnataka India
- Assistant Professor Department of Mathematics Siddaganga Institute of Technology, Tumakuru Karnataka India
- Associate Professor , Department of Mathematics Government First Grade College, Tumkur, Karnataka India
- Department of Information Technology, Sanjivani College of Engineering, Savitribai Phule Pune University Maharashtra India
Abstract
This investigation proposes a methodology to optimize biohybrid polymer synthesis using fuzzy inference systems (FIS). The study combines fuzzy logic principles with mathematical calculations for finding the best synthesis parameters to enhance the synthesis quality. This study consists on a sample about the use of FIS on optimisation of polymer synthesis, where they show the process of fuzzification, rule base creation, inference mechanism and defuzzification using the centroid method through experimental data. The results revealed that the FIS is a powerful tool to deal with uncertainty and vagueness inherent in polymer synthesis; it is capable of sharpening the output that shows the optimized synthesis parameters. Our evolutionary-derived-synthesis optimization increases efficiency and quality, the sharp output value being roughly 0.802. In addition, this provides environmental advantages due to more energy acting as a communication well between resources and to make less polymeric waste within the polymerization process. In discussing the benefits of using FIS, the study appropriates expert knowledge and experimental data, while also discussing certain limitations and challenges in FIS implementation. These findings contribute original, important results to polymer science and engineering, by providing a systematic, EE strategy that can be used in the synthesis of polymers, using FL techniques to optimize processes.
Keywords: Polymer synthesis, Fuzzy inference system, Optimization, Fuzzy logic, Synthesis quality, Materials science, Process optimization, Computational intelligence.
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Journal of Polymer and Composites
| Volume | |
| Received | May 24, 2024 |
| Accepted | June 18, 2024 |
| Published | July 11, 2024 |
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