Adaptive Data‐Driven Modeling Strategy Based on Feature Selection for an Industrial Natural Gas Sweetening Process
Wei Jiang,
Jinjin Li,
Guanshan Chen
et al.
Abstract:As the core process of natural gas purification plant, natural gas sweetening directly affects the production efficiency and product quality of the purification plant. However, process modeling based on sulfur content prediction presents challenges in adaptability and accuracy. To tackle this, a machine learning‐based modeling approach is proposed that integrates an adaptive immune genetic algorithm with random forest (RF) to intelligently select process features as input variables for RF modeling. The industr… Show more
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