Application of least square support vector machines in the prediction of aeration performance of plunging overfall jets from weirs

Aeration is a mass transfer process between the atmosphere and water. Aeration is used for water quality enhancement in sewage treatment plants and in polluted rivers and lakes. This can be enhanced by creating turbulence in the water. Plunging overfall jets from weirs are a particular instance of producing such turbulence. In this paper, two intelligent models are realized to predict the air entrainment rate and aeration efficiency of weirs. Least square support vector machine (LS-SVM) is used as intelligent tool. Threefold cross validation test method is used to evaluate the performance of LS-SVM models. The correlation between predicted and measured values is found 0.99 for air entrainment rate and 0.98 for aeration efficiency. The test results indicate that the LS-SVM can be used successfully in predicting the air entrainment rate and aeration efficiency of weirs. Moreover, the performances of the LS-SVM models are compared with multi nonlinear and linear regression models.