2023-03-07
Comparative analysis of data using machine learning algorithms: A hydroponics system use case
2023-03-07 • Godwin Idoje, Christos Mouroutoglou, Tasos Dagiuklas, Anastasios Kotsiras, Muddesar Iqbal, Panagiotis Alefragkis
This paper makes a comparison of machine learning algorithms for the analysis of four hydroponic datasets. Data have been gathered daily from hydroponic systems to predict the output of the hydroponic systems. This research compares the performance of the federated split Learning, Deep neural network, extreme Gradient Boosting (XGBoost), and Linear regression algorithms on four different hydroponic systems. These algorithms have been used to analyze the datasets of Nutrient Film Technic (NFT), Floating (FL), Aggre…