###
工程科学与技术:2016,48(5):167-172
←前一篇   |   后一篇→
本文二维码信息
码上扫一扫!
模糊系统结合蚁群算法的金具温升建模
(1.平高集团有限公司;2.西安工业大学 材料与化工学院)
Modeling the Rise of Temperature of Fitting by Combining Fuzzy System and Ant Colony Algorithm
(1.Pinggao Group Co.,Ltd.;2.School of Materials and Chemical Eng. of Xi’an Technological Univ.)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1382次   下载 347
投稿时间:2015-07-27    修订日期:2016-06-01
中文摘要: 为了得到准确可靠的阀厅连接金具温升模型,运用模糊系统结合蚁群算法的方法进行建模。在分析基本蚁群算法与梯度下降法优缺点的基础上,将两种方法结合形成改进蚁群算法,即在基本蚁群算法基础上应用梯度下降算法。通过试验得到的训练数据分别用基本蚁群算法、梯度下降算法、改进蚁群算法训练模糊系统,改进蚁群算法的收敛效果优于其他两种方法;通过试验得到的测试数据对4种方法所得的模型进行测试,由改进蚁群算法训练模糊系统所得模型的测试效果是最好的。结果表明,若能通过试验得到足量训练数据,用改进蚁群算法训练模糊系统的方法对阀厅连接金具的温升进行建模是可行的。
Abstract:In order to get an accurate and reliable model of the rise of temperature of connection fitting in value hall of UHVDC,a method of fuzzy system combined ant colony algorithm was used.After analyzing the characteristics of basic ant colony algorithm and gradient descent algorithm,an improved ant colony algorithm was put forward by combining basic ant colony algorithm and gradient descent algorithm,in which gradient descent algorithm was processed after basic ant colony algorithm. Through training data obtained from experiment,the fuzzy system was trained by basic ant colony algorithm,gradient descent algorithm and improved ant colony algorithm respectively.The convergence effect of improved ant colony algorithm was better than that of other two algorithms.All models were tested by testing data obtained from experiment,and the prediction effect of the fuzzy system trained by improved ant colony algorithm was best of all models.The prediction results showed that if training data obtained from experiment was enough,the fuzzy system trained by improved ant colony algorithm was reliable to predict the rise of temperature of connection fitting.
文章编号:201500737     中图分类号:    文献标志码:
基金项目:国家高技术研究发展计划资助项目(2014AA051802) ;国家电网科技资助项目(SGNXJX00YJJS1400105)
作者简介:
引用文本:
王刚,谭盛武,林生军,何子博,常林晶,杨国华.模糊系统结合蚁群算法的金具温升建模[J].工程科学与技术,2016,48(5):167-172.
Wang Gang,Tan Shengwu,Lin Shengjun,He Zibo,Chang Linjing,Yang Guohua.Modeling the Rise of Temperature of Fitting by Combining Fuzzy System and Ant Colony Algorithm[J].Advanced Engineering Sciences,2016,48(5):167-172.