摘要
本文详细介绍了基于GA-BP神经网络在垃圾焚烧过程中二噁英排放软测量的应用过程。采用基于GA-BP神经网络理论来建立二噁英排放的软测量模型,通过软测量方法的结果和实际值的分析比较,表明基于GA-BP神经网络的二噁英软测量模型的测量精度较高、容错性好、泛化能力较好,是防止垃圾焚烧过程带来的二次污染有效的方法,为垃圾的焚烧过程控制提供了指导依据。此方法可以有效地应用于其它不能直接测量的工程应用。
This paper introduces the modeling application of Dioxin emission from MSW process by GA based artificial nueral network. This paper establishes the soft measurement model of Dioxin emission using Ga based BP nueral network theory. Comparing between the soft measure value and actual value. The soft measurement result indicates that the soft measurement model of Dioxin emission has a highly accurate and better generalization. It can provide reference and determination for MSW process. It can prevent the second air pol- lution during the inceneration and provide guidance of process control. This model can also be used effectively in other fields.
出处
《微计算机信息》
北大核心
2008年第21期222-224,233,共4页
Control & Automation
基金
云南省科技计划项目(2001GG19)
云南省教育厅科学研究基金项目(5Z0529D
5Z1131G)
关键词
遗传算法
BP神经网络
二噁英排放软测量模型
Genetic algorithm
Back Propagation nueral network
soft measurement model of Dioxin emission