Application of Machine Learning Techniques in Aquaculture
This work addresses data analysis challenges in aquaculture, but it appears incremental as it applies existing methods without novel contributions.
The paper applies various machine learning algorithms to historical aquaculture data, such as farm practices and environmental factors, to identify associations between variables, but does not report specific results or numbers.
In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.