基于改进GA-BP神经网络的工厂污水监测系统研究Research on factory sewage monitoring system based on improved GA-BP neural network
诸飞,俞阿龙
摘要(Abstract)：
针对工厂污水水质评价准确性低、实时性差等问题,提出一种将改进遗传算法(GA)和BP神经网络相结合对工厂污水的水质进行评价的方法。GA-BP神经网络不仅具有BP神经网络的非线性映射能力,还具有遗传算法的全局搜索能力。采用自适应算法对GA的交叉率和变异率进行改进,用GA优化BP的权值和阈值,将最优权值和阈值送给BP神经网络进行训练、预测,并与传统BP进行比较。实验结果表明,改进的GA-BP神经网络无论是收敛性、准确性还是实时性都优于传统BP网络。该方法用于污水水质评价具有应用推广价值。
关键词(KeyWords)： 工厂污水;水质分类;改进GA;BP神经网络;污水监测;自适应算法
基金项目(Foundation): 国家自然科学基金资助项目(61350008);; 江苏省高校产业化推进项目(JHB2012-55);; 国家星火计划(2012GA690166)~~
作者(Author): 诸飞,俞阿龙
DOI: 10.16652/j.issn.1004-373x.2018.11.030
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