E3S Web Conf.
Volume 271, 20212021 2nd International Academic Conference on Energy Conservation, Environmental Protection and Energy Science (ICEPE 2021)
|Number of page(s)||4|
|Section||Environmental Materials and Solid Waste Recycling Technology|
|Published online||15 June 2021|
Prediction Method of Wax Deposition Rate in Crude Oil Pipeline Based on RBF Neural Network and Support Vector Machine
College of Energy and Environmental Engineering, Shandong Huayu University of Technology, Dezhou, Shandong, China
a Corresponding author: email@example.com
Wax-bearing crude oil will precipitate wax crystals in pipeline transportation, which will cause hidden dangers and affect the economic benefits of the pipeline. In order to study the complex wax deposition on the pipe wall and calculate the wax deposition under other conditions, this paper uses RBF neural network and support vector machine to predict the wax deposition data in Huachi operation area. The results show that the errors of the two methods meet the requirements. Because support vector machine can model and calculate finite samples, it is found that the accuracy of support vector machine is higher.
© The Authors, published by EDP Sciences, 2021
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