A hybrid intelligent method for three-dimensional short-term prediction of dissolved oxygen content in aquaculture

<div><p>A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content prediction model based on a radial basis function (RBF) neural network, K-means and subtractive clustering was developed and named the subtractive clustering (SC)-K-means-RBF model. In this modeling process, K-means and subtractive clustering methods were employed to enhance the hyperparameters required in the RBF neural network model. The comparison of the predicted results of different traditional models validated the effectiveness and accuracy of the proposed hybrid SC-K-means-RBF model for three-dimensional prediction of dissolved oxygen content. Consequently, the proposed model can effectively display the three-dimensional distribution of dissolved oxygen content and serve as a guide for feeding and future studies.</p></div

Topology structure diagram of the digital wireless system.

<p>Topology structure diagram of the digital wireless system.</p

Structure of RBF[22].

<p>Structure of RBF[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192456#pone.0192456.ref022" target="_blank">22</a>].</p

The process of parameter selection for the RBF neural network.

<p>The process of parameter selection for the RBF neural network.</p

Training and test data.

<p>Training and test data.</p

Cross-section of the spatial distribution of dissolved oxygen in the aquaculture pond.

<p>Cross-section of the spatial distribution of dissolved oxygen in the aquaculture pond.</p

Curved surface of dissolved oxygen of 2 mg/L.

<p>Curved surface of dissolved oxygen of 2 mg/L.</p

The process of the three-dimensional model for dissolved oxygen content.

<p>The process of the three-dimensional model for dissolved oxygen content.</p

Training results for dissolved oxygen content prediction using the SC-K-means-RBF model.

<p>Training results for dissolved oxygen content prediction using the SC-K-means-RBF model.</p

Error statistics of the four forecasting models.

<p>Error statistics of the four forecasting models.</p