Fuzzy Inference System to Improve Catfish Care in Bioflok Pools Based on Temperature and Water Quality
DOI:
https://doi.org/10.62535/c6c50w10Keywords:
Fuzzy , Biofloc, Clarias gariepinus, catfishTechnology and management of fish hatcheriesAbstract
The study explores the application of the Fuzzy Inference System (FIS) to improve the
maintenance of clay (Clarias gariepinus) in Biofloc ponds, focusing on critical factors such as
temperature and water quality. In the context of the efficiency of the biofloc system in water quality
management, the study addresses the challenges posed by dynamic environmental conditions.
Through a comprehensive gap analysis, the study identifies disparities between current research
and the need for a specialized approach that integrates FIS for adaptive decision-making. The
urgency stems from the limited coverage of previous research in addressing temperature dynamics
and water quality. This research places itself in the research landscape by supporting and refining
previous findings and introducing new FIS applications. The integration of Fuzzy Logic into bio
floc management decision-making is new in this study. This research, supported by the latest
literature from leading journals, emphasizes the significance and originality of its approach,
contributing to sustainable and adaptive aquaculture practices.
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