Hybrid Intelligent Model for Predicting Corrosion Rate of Carbon Steel in CO2 Environments DOI Open Access
Zhihao Qu, Xiaoxiao Zou, Guoqing Xiong

и другие.

Materials and Corrosion, Год журнала: 2025, Номер unknown

Опубликована: Март 23, 2025

ABSTRACT This study aims to construct a prediction model for the internal corrosion rate of offshore pipelines in CO 2 environments, with intention providing effective and protection strategies oil gas industry. By conducting investigative analysis integrating experimental data, principal component (PCA) was employed extract primary influencing factors, which were used as input variables support vector regression (SVR) output variable. The particle swarm optimization (PSO) algorithm utilized optimize hyperparameters model, enhancing accuracy. results indicate that first eight components account 95.9% cumulative contribution, optimized SVR achieved correlation coefficient (R ) exceeding 0.90. Compared other models methods, PCA PSO effectively predicts pipelines, offering theoretical protection.

Язык: Английский

Hybrid Intelligent Model for Predicting Corrosion Rate of Carbon Steel in CO2 Environments DOI Open Access
Zhihao Qu, Xiaoxiao Zou, Guoqing Xiong

и другие.

Materials and Corrosion, Год журнала: 2025, Номер unknown

Опубликована: Март 23, 2025

ABSTRACT This study aims to construct a prediction model for the internal corrosion rate of offshore pipelines in CO 2 environments, with intention providing effective and protection strategies oil gas industry. By conducting investigative analysis integrating experimental data, principal component (PCA) was employed extract primary influencing factors, which were used as input variables support vector regression (SVR) output variable. The particle swarm optimization (PSO) algorithm utilized optimize hyperparameters model, enhancing accuracy. results indicate that first eight components account 95.9% cumulative contribution, optimized SVR achieved correlation coefficient (R ) exceeding 0.90. Compared other models methods, PCA PSO effectively predicts pipelines, offering theoretical protection.

Язык: Английский

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