文献类型：会议论文

英文题名：Early Warning Technology for Cracking Severity Based on Improved Cultural Differential Algorithm

作者：Pu, Yunxia[1];Liu, Mandan[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

会议论文集：8th World Congress on Intelligent Control and Automation (WCICA)

会议日期：JUL 06-09, 2010

会议地点：Jinan, PEOPLES R CHINA

语种：英文

外文关键词：Cultural Algorithms; Differential Evolution Algorithm; Elman Neural Network; Cracking Severity; Early Warning; Ethylene

摘要：Effective monitoring and early warning for cracking severity are directly related to the ethylene production stability and the overall economic benefits. Elman neural network is used to establish the early warning model of cracking severity, and an improved Cultural Differential Evolution algorithm(ICDE) is proposed to training the model. This hybrid algorithm integrates Cultural algorithm(CA) and Differential Evolution algorithm(DE) together, and increases some measure indicators of evolution direction, to make the algorithm more adaptive. Simulation results show that this method gains accurate warning signals to the cracking working conditions timely and effectively, obtained satisfactory results.