Predicting the Characteristics of Biofouling Mass Based on Support Vector Machine

Abstract:

A new prediction model of material chemical character effects on biofouling mass was built based on Support Vector Machine (SVM), in which there were four input vectors, which were carbon content, hydrogen content and oxygen content of the solid materials and flow rate, and one output vectors, which was the average amount of biofouling formed on the solid surface. Firstly, creating the sample database and normalizing all samples. Secondly, training the model based on the training samples to obtain the optimal prediction model, then, predicting the training samples. Comparing with experimental results, the accuracy of the SVM model is 95.5%. Besides, the model was tested by poly (ethylene terephthalate), and the predicted and actual results are consistent. Thus, the construction of the predictive model is reasonable and feasible.

• Periodical: Applied Mechanics and Materials (Volume 459)
• Pages: 60-64
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.459.60
• Online since: October 2013
• Authors: Xiao Qiang Wen*
• Keywords: Biofouling, Material Chemical Characteristic, Prediction, Supporting Vector Machine

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