Qi Zhuanga,*
, Zhuo Chenb, Dong Liuc, Yangyang Tiand
Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-8, 2022, DOI:10.5098/hmt.19.19
Abstract In order to improve the accuracy and efficiency of wax deposition rate prediction of waxy crude oil in pipeline transportation, A GRA-IPSO-ELM
model was established to predict wax deposition rate. Using Grey Relational Analysis (GRA) to calculate the correlation degree between various factors
and wax deposition rate, determine the input variables of the prediction model, and establish the Extreme Learning Machine (ELM) prediction model,
improved particle swarm optimization (IPSO) is used to optimize the parameters of ELM model. Taking the experimental data of wax deposition in
Huachi operation area as an example, the prediction performance More >
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