Gaussian Distribution Model for Detecting Dangerous Operating Conditions in Industrial Fish Farming

Autor:	Luís Cicero Bezerra da Silva, Bruna Daniela Mendes Lopes, Isidro Manuel Blanquet, Carlos Alberto Ferreira Marques
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	data processing mathematical models probability and statistics Gaussian distribution model industrial fish farming Technology Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Zdroj:	Applied Sciences, Vol 11, Iss 13, p 5875 (2021)
Druh dokumentu:	article
ISSN:	11135875 2076-3417
DOI:	10.3390/app11135875
Popis:	The development of better monitoring technologies, the early combat of outbreaks, massive mortality, and promoting sustainability are challenges that the aquaculture industry still faces, and the development of solutions for this is an open problem. In this paper, focusing our attention on monitoring technologies as a promising solution to these issues, we report a Gaussian distribution model for detecting dangerous operating conditions in industrial fish farming. This approach allows us to indicate through a 2D image visualization when fish production is under normal, warning, or dangerous operating conditions. Furthermore, our proposed method has promising possibilities for application in the most varied fields of science, given that the mathematical procedure described allows us to discover the fundamental statistical structure of physical, chemical, and biological systems governed by laws of a probabilistic nature.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/fccc242f755a48a4bcab20a743bec035 Zobrazit plný text záznamu View record in DOAJ