Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya

<div>FNN-based predictions of DO with (a) EC, TP, and TN; (b) EC, TP, TN, and pH; (c) EC, TP, TN, pH, and temperature; and (d) eight (8) input WQ parameters.</div>

Complexity

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Figure 10

Figure 10: Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya 

Figure 10 | Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya 