Underground space optimization of smart city based on information processing technology

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-04-26 DOI:10.3233/JIFS-189939
Zhiyong Li
{"title":"Underground space optimization of smart city based on information processing technology","authors":"Zhiyong Li","doi":"10.3233/JIFS-189939","DOIUrl":null,"url":null,"abstract":"This study explores the underground space optimization method of smart city based on information processing technology to save space optimization operation time. Taking coordinate of intersection point, radius of intersection point, mileage of vertical slope change point and elevation of slope change point as design variables, taking total cost of underground space construction of smart city as objective function and taking plane, vertical section, horizontal and vertical combination and environmental impact as constraint conditions, a multi-objective optimization mathematical model of underground space of smart city was constructed. Parete genetic algorithm in information processing technology was used to solve the multi-objective optimization mathematical model of the underground space of smart city, realize the automatic search for the optimal scheme of the underground space of smart city, and complete the intelligent optimization process of the underground space construction scheme of smart city. The results show that the method obtained from this study can effectively optimize the underground space of smart city and obtain the optimal subway laying line, save space and optimize operation time and improve the convergence of the method.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"19 1","pages":"1-7"},"PeriodicalIF":1.5000,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-189939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

This study explores the underground space optimization method of smart city based on information processing technology to save space optimization operation time. Taking coordinate of intersection point, radius of intersection point, mileage of vertical slope change point and elevation of slope change point as design variables, taking total cost of underground space construction of smart city as objective function and taking plane, vertical section, horizontal and vertical combination and environmental impact as constraint conditions, a multi-objective optimization mathematical model of underground space of smart city was constructed. Parete genetic algorithm in information processing technology was used to solve the multi-objective optimization mathematical model of the underground space of smart city, realize the automatic search for the optimal scheme of the underground space of smart city, and complete the intelligent optimization process of the underground space construction scheme of smart city. The results show that the method obtained from this study can effectively optimize the underground space of smart city and obtain the optimal subway laying line, save space and optimize operation time and improve the convergence of the method.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于信息处理技术的智慧城市地下空间优化
本研究探索基于信息处理技术的智慧城市地下空间优化方法,节省空间优化运行时间。以交点坐标、交点半径、垂直变坡点里程和变坡点标高为设计变量,以智慧城市地下空间建设总成本为目标函数,以平面、纵断面、水平和垂直组合以及环境影响为约束条件,构建了智慧城市地下空间多目标优化数学模型。利用信息处理技术中的Parete遗传算法求解智慧城市地下空间多目标优化数学模型,实现对智慧城市地下空间最优方案的自动搜索,完成智慧城市地下空间建设方案的智能优化过程。结果表明,本研究所得方法能够有效地优化智慧城市地下空间,获得最优地铁敷设线路,节省空间,优化运行时间,提高方法的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
期刊最新文献
Four Types of Generalized Fuzzy Continuous Mappings Analytic Review of Healthcare Software by Using Quantum Computing Security Techniques Hybrid Metaheuristic Technique for Optimization of Virtual Machine Placement in Cloud Complex Fuzzy Rough Aggregation Operators and their Applications in EDAS for Multi-Criteria Group Decision-Making Efficient Multi-Task CNN for Face and Facial Expression Recognition Using Residual and Dense Architectures for Application in Monitoring Online Learning
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1