Forecasting Corrosion Rate of Coolingwater Based on Least Squares Support Vector Machine

Abstract

In view of the corrosion of cooling water system, the dynamic simulation test was conducted with the cooling water dynamic simulation experiment device. In the test period the corrosion rate and the water quality factors were monitored. Based on the test data, an intelligent prediction model of cooling water corrosion rate based on least squares support vector machine (LS-SVM) is constructed, in which the water quality factors related with corrosion were selected as input variables and the corrosion rate was selected as output variable. The results show that the LS-SVM model is pithily, and it has better extensive capability than traditional methods. The new method is effective and reliable, and it can be viewed as a new approach to advance the development of cooling water treatment technology and improve the prediction accuracy of the corrosion rate.