EventsThe 4th International Electronic Conference on Applied Sciences
Published
This submission belongs to the session I. A Student Session of the event The 4th International Electronic Conference on Applied Sciences
Published date
09 Nov, 2023
Academic Editor
author-avatarNunzio Cennamo
Citation
Beatriz Pereira Silva, Ernandes Benedito Pereira, Fábio De Oliveira Neves, Development of Decision-Making Methods for Bioenergy Production from Microorganisms, in Proceedings of The 4th International Electronic Conference on Applied Sciences, 27 October–10 November 2023, MDPI: Basel, Switzerland, doi: 10.3390/ASEC2023-15958
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Development of Decision-Making Methods for Bioenergy Production from Microorganisms

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Ernandes Benedito Pereira 2
1. Department of Biotechnology. Institute of Exact Sciences, Federal University of Alfenas, Alfenas, Minas Gerais State, Brazil
2. Pharmaceutical Sciences Faculty. Food and Medicine Department. Federal University of Alfenas, Alfenas, Minas Gerais State, Brazil
3. Department of Environmental Science. Institute of Exact Sciences, Federal University of Alfenas, Alfenas, Minas Gerais State, Brazil
Abstract

Society relies mainly on fossil fuels for energy generation, which results in risks due to geopolitical conflicts, environmental damage, and climate change. By opting for renewable energy sources, including bioenergy derived from microorganisms, there is a potential solution to this predicament. By harnessing the energy-producing abilities of microorganisms, it is possible to generate renewable energy on a large scale without harming the environment or human activities. Thereby, the present work has as a neuralgic objective to develop a decision-making method for microbial energy generation. Using as a method the fuzzy logic of the Mamdani type for absorbing the uncertainties and inaccuracies, characteristic of this work theme. A structure with 4 levels of indicators was developed, using triangular and trapezoidal functions at the ends. In the development of the fuzzy rules, were used 5 input fuzzy sets and 5 output fuzzy sets when there were two indicators in the fuzzy machinery and three input fuzzy sets and 5 output fuzzy sets with 3 or more indicators in the fuzzy machinery. Five scenarios were developed, considering a scale of 0 to 10: High criticality (10-8), Tolerable (8-6), Adequate (6-4), Desirable (4-1.5) and Low criticality (1.5-0). Thus, it is expected that this model can optimize decision-making processes and promote renewable energy alternatives, potentially reducing the dependence on fossil fuels in the future.

Keywords
Bioenergy
Microorganisms
Logic Fuzzy
Energy Scenarios.
Manuscript
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