Classification based on fuzzy inference systems for artificial habitat quality in shrimp farming

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Abstract

Nowadays, the methods based on fuzzy inference systems (FIS) have demonstrated to be useful in the treatment of biological problems. An ecological abstract model for classifying artificial habitat quality in shrimp farming has been developed, based on a water quality index calculated with fuzzy reasoning. The potential application of the fuzzy index has been tested with a case of study proving the importance of the artificial intelligence in this area. The results show a good response obtaining four classifications of the status of the water quality; excellent, good, regular or poor. Therefore, this model emerges as a suitable and alternative tool to be used in the effective treatment of the water management in shrimp aquaculture. © 2008 IEEE.
Original languageAmerican English
Pages388-392
Number of pages348
DOIs
StatePublished - 29 Dec 2008
Externally publishedYes
Event7th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2008 -
Duration: 29 Dec 2008 → …

Conference

Conference7th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2008
Period29/12/08 → …

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  • Cite this

    Carbajal, J. J., & Śanchez, L. P. (2008). Classification based on fuzzy inference systems for artificial habitat quality in shrimp farming. 388-392. Paper presented at 7th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2008, . https://doi.org/10.1109/MICAI.2008.70