Machine Learning
An expert system for predicting aeration performance of weirs by using ANFIS
Expert Systems with Applications: An International Journal
Advances in Engineering Software
Using intelligent methods to predict air-demand ratio in venturi weirs
Advances in Engineering Software
An optimal method for prediction and adjustment on byproduct gas holder in steel industry
Expert Systems with Applications: An International Journal
Model selection for least squares support vector regressions based on small-world strategy
Expert Systems with Applications: An International Journal
Predicting high-tech equipment fabrication cost with a novel evolutionary SVM inference model
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Computers and Electronics in Agriculture
Hi-index | 12.06 |
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.