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What is Hybrid Model for Pipeline Corrosion Prediction about?

This study presents a new hybrid algorithm model, PCA-CPSO-SVR, for predicting the internal corrosion rate of multiphase pipelines, combining support vector regression (SVR), principal component analysis (PCA), and chaos particle swarm optimization (CPSO). The model demonstrates improved prediction accuracy with a mean absolute error of 0.083, which is 18.6% lower than traditional SVR methods. Compared to five benchmark models, PCA-CPSO-SVR shows superior performance in predicting corrosion rates, highlight

Author

silverrafael

Language

EN