Dissolved Oxygen Prediction Using Support Vector Machine in Terengganu River

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At Terengganu River, Malaysia, a study was conducted to predict Dissolved Oxygen using SVM. They conducted the study for two different stations using the five parameters such as, pH, temperature, electrical conductivity and Nitrate and Ammonia Nitrogen. They used SVM with its non-linear and stochastic modelling proficiencies. The performance of the model was evaluated using three statistical indexed such as, Mean Squared Error (MSE), Coefficient of Efficiency (CE) and coefficient of Correlation (CC). They concluded that SVM can give robust and precise result and able to give fairly accurate predictions. It can also help in optimizing the water quality monitoring programs.

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