关键词: 乙烯裂解深度;模糊核聚类, 最小二乘支持向量机, 多模型建模

Abstract: Modeling and control of ethylene cracking severity is very important to the real-time optimization of cracking furnace. To address the problem with the complexity and volatility of Naphtha feedstock components, fuzzy kernel clustering method was developed to divide the naphtha database optimally. After establishing multiple models of least squares support vector machine, in order to improve the model accuracy and generalization ability, differential evolution algorithm was used to determine the proper parameters of LSSVM model. We established each sub-model based on the sub-condition in ethylene cracking process, also the switching strategy is based on weighted value. The simulation results on the real industrial data showed that DE-LSSVM multiple models of ethylene cracking severity based on fuzzy kernel clustering got good tracking performance and high accuracy.

Key words: ethylene cracking severity, fuzzy kernel clustering, least squares support vector machine, multiple modeling