基于遗传算法的锅炉温度场重构算法研究

Shuang-zhou Guo, Jin-lan Liang
{"title":"基于遗传算法的锅炉温度场重构算法研究","authors":"Shuang-zhou Guo, Jin-lan Liang","doi":"10.1109/icomssc45026.2018.8941904","DOIUrl":null,"url":null,"abstract":"Based on the boiler temperature field reconstruction algorithm of acoustics principle, a temperature field reconstruction algorithm with genetic algorithm is proposed in this paper. Under laboratory condition, the reconstruct temperature field algorithm in use of genetic algorithm is simulated. Using genetic algorithm to interpolate the grid and fitting the measuring temperature field reconstruction is to achieve treatment, and the advantages of genetic algorithms reconstruction figure is confirmed. Meanwhile, the application of genetic algorithm reconstructs the acoustic temperature field with a curved effect on the transmission path. Finally, the reconstruction temperature field of the genetic algorithm draws the conclusion of high accuracy temperature field and faster reconstruction speed with the maximum error, maximum relative error of evaluation, the average error and root mean square error of the algorithm. The simulation results show that the temperature field reconstruction algorithm using genetic algorithms has the higher accuracy and faster reconstruction speed compared with the method of least squares algorithm for image reconstruction results.","PeriodicalId":332213,"journal":{"name":"2018 International Computers, Signals and Systems Conference (ICOMSSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Boiler Temperature Field Reconstruction Algorithm Based on Genetic Algorithm\",\"authors\":\"Shuang-zhou Guo, Jin-lan Liang\",\"doi\":\"10.1109/icomssc45026.2018.8941904\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the boiler temperature field reconstruction algorithm of acoustics principle, a temperature field reconstruction algorithm with genetic algorithm is proposed in this paper. Under laboratory condition, the reconstruct temperature field algorithm in use of genetic algorithm is simulated. Using genetic algorithm to interpolate the grid and fitting the measuring temperature field reconstruction is to achieve treatment, and the advantages of genetic algorithms reconstruction figure is confirmed. Meanwhile, the application of genetic algorithm reconstructs the acoustic temperature field with a curved effect on the transmission path. Finally, the reconstruction temperature field of the genetic algorithm draws the conclusion of high accuracy temperature field and faster reconstruction speed with the maximum error, maximum relative error of evaluation, the average error and root mean square error of the algorithm. The simulation results show that the temperature field reconstruction algorithm using genetic algorithms has the higher accuracy and faster reconstruction speed compared with the method of least squares algorithm for image reconstruction results.\",\"PeriodicalId\":332213,\"journal\":{\"name\":\"2018 International Computers, Signals and Systems Conference (ICOMSSC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Computers, Signals and Systems Conference (ICOMSSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icomssc45026.2018.8941904\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Computers, Signals and Systems Conference (ICOMSSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icomssc45026.2018.8941904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文在声学原理锅炉温度场重构算法的基础上,提出了一种基于遗传算法的锅炉温度场重构算法。在实验室条件下,对利用遗传算法重构温度场的算法进行了仿真。利用遗传算法对网格进行插值和拟合,实现了测量温度场重构的处理,并证实了遗传算法重构图的优势。同时,应用遗传算法重构了对传输路径产生弯曲效应的声温度场。最后,对遗传算法的重构温度场进行了研究,得出了该算法的最大误差、最大评价相对误差、平均误差和均方根误差具有较高的温度场精度和较快的重构速度的结论。仿真结果表明,与最小二乘算法相比,采用遗传算法的温度场重建算法具有更高的精度和更快的重建速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Boiler Temperature Field Reconstruction Algorithm Based on Genetic Algorithm
Based on the boiler temperature field reconstruction algorithm of acoustics principle, a temperature field reconstruction algorithm with genetic algorithm is proposed in this paper. Under laboratory condition, the reconstruct temperature field algorithm in use of genetic algorithm is simulated. Using genetic algorithm to interpolate the grid and fitting the measuring temperature field reconstruction is to achieve treatment, and the advantages of genetic algorithms reconstruction figure is confirmed. Meanwhile, the application of genetic algorithm reconstructs the acoustic temperature field with a curved effect on the transmission path. Finally, the reconstruction temperature field of the genetic algorithm draws the conclusion of high accuracy temperature field and faster reconstruction speed with the maximum error, maximum relative error of evaluation, the average error and root mean square error of the algorithm. The simulation results show that the temperature field reconstruction algorithm using genetic algorithms has the higher accuracy and faster reconstruction speed compared with the method of least squares algorithm for image reconstruction results.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信