铸造技术2017，Vol.38Issue(8)：1936-1939,4.DOI:10.16410/j.issn1000-8365.2017.08.043
薄板连铸GA-LM-BP漏钢预报模型研究
Breakout Prediction in Thin Slab Continuous Casting Process Based on GA-LM-BP Neural Network
摘要
Abstract
Slow convergence and local optimal solution in the training process are two terrible drawbacks of the traditional BP neural network.The global optimization ability of genetic algorithm and the local optimization ability of LM algorithm were introduced into the training process of the BP neural network to improve its converge property,and then a GA-LM-BP neural network was established.The GA-LM-BP neural network model was trained and tested with the historical data collected trom a steel plant.The testing results show that the convergence rate of the GA-LM-BP neural network model is faster than the traditional BP neural network significantly.The generalization capability and the recognition accuracy for the temperature characteristics of the breakout prediction system are greatly improved after using GA-LM-BP neural network.关键词
薄板连铸/漏钢预报/遗传算法/LM算法/BP神经网络Key words
thin slab continuous casting/breakout prediction/genetic algorithm/LM algorithm/BP neural network分类
冶金工业引用本文复制引用
张本国,展邦华,刘军,夏建生..薄板连铸GA-LM-BP漏钢预报模型研究[J].铸造技术,2017,38(8):1936-1939,4.基金项目
江苏省基础研究计划资助项目(BK20150429) （BK20150429）
国家自然科学基金资助项目(51505408) （51505408）
