摘要
在本次研究中通过提出一种铜闪速熔炼操作模式的智能优化方法,一种借助动态化T-2递归模糊神经网络,实现软测量工艺参数的系统。另外该系统还能够借助模式分解法,分解海量数据之后借助基于神经网络及混沌遗传算法的铜闪速熔炼操作模式智能优化方法,优化模式子集。此种方法在铜闪速熔炼操作模式系统中,发现能够对铜闪速炉的生产效率有效提升。
In this study, an intelligent optimization method for copper flash smelting operation mode is proposed, and a system for soft measurement process parameters is realized by means of dynamic T-2 recursive fuzzy neural network.In addition, the system can also decompose massive data by means of the model decomposition method, and then optimize the mode subset by means of the intelligent optimization method of copper flash smelting operation mode based on neural network and chaotic genetic algorithm.This method has been found to effectively improve the production efficiency of copper flash furnaces in the copper flash smelting operation mode system.
引文
[1]阳春华,王晓丽,陶杰,等.铜闪速熔炼配料过程建模与智能优化方法研究[J].系统仿真学报,2018,20(8):2152-2155.
[2]桂卫华,刘建华,谢永芳.铜闪速熔炼过程操作模式分级匹配技术与演化策略[J].系统工程理论与实践,2016,33(10):2714-2720.