Predicting the External Corrosion Rate of Buried Pipelines Using a Novel Soft Modeling Technique
Zebei Ren,
Kun Chen,
Dongdong Yang
et al.
Abstract:External corrosion poses a significant threat to the integrity and lifespan of buried pipelines. Accurate prediction of corrosion rates is important for the safe and efficient transportation of oil and natural gas. However, limited data availability often impacts the performance of conventional predictive models. This study proposes a novel composite modeling approach integrating kernel principal component analysis (KPCA), particle swarm optimization (PSO), and extreme learning machine (ELM). The key innovatio… Show more
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