铁路线形优化三维环境适宜性分析的地理信息模型

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Hao Pu, Xinjie Wan, Taoran Song, P. Schonfeld, Wei Li, Jianping Hu
{"title":"铁路线形优化三维环境适宜性分析的地理信息模型","authors":"Hao Pu, Xinjie Wan, Taoran Song, P. Schonfeld, Wei Li, Jianping Hu","doi":"10.3233/ica-220692","DOIUrl":null,"url":null,"abstract":"Railway alignment design is a complicated problem affected by intricate environmental factors. Although numerous alignment optimization methods have been proposed, a general limitation among them is the lack of a spatial environmental suitability analysis to guide the subsequent alignment search. Consequently, many unfavorable regions in the study area are still searched, which significantly degrades optimization efficiency. To solve this problem, a geographic information model is proposed for evaluating the environmental suitability of railways. Initially, the study area is abstracted as a spatial voxel set and the 3-D reachable ranges of railways are determined. Then, a geographic information model is devised which considers topographic influencing factors (including those affecting structural cost and stability) as well as geologic influencing factors (including landslides and seismic impacts) for different railway structures. Afterward, a 3-D environmental suitability map can be generated using a multi-criteria decision-making approach to combine the considered factors. The map is further integrated into the alignment optimization process based on a 3-D distance transform algorithm. The proposed model and method are applied to two complex realistic railway cases. The results demonstrate that they can considerably improve the search efficiency and also find better alignments compared to the best alternatives obtained manually by experienced human designers and produced by a previous distance transform algorithm as well as a genetic algorithm.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":"67 1","pages":"67-88"},"PeriodicalIF":5.8000,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A geographic information model for 3-D environmental suitability analysis in railway alignment optimization\",\"authors\":\"Hao Pu, Xinjie Wan, Taoran Song, P. Schonfeld, Wei Li, Jianping Hu\",\"doi\":\"10.3233/ica-220692\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Railway alignment design is a complicated problem affected by intricate environmental factors. Although numerous alignment optimization methods have been proposed, a general limitation among them is the lack of a spatial environmental suitability analysis to guide the subsequent alignment search. Consequently, many unfavorable regions in the study area are still searched, which significantly degrades optimization efficiency. To solve this problem, a geographic information model is proposed for evaluating the environmental suitability of railways. Initially, the study area is abstracted as a spatial voxel set and the 3-D reachable ranges of railways are determined. Then, a geographic information model is devised which considers topographic influencing factors (including those affecting structural cost and stability) as well as geologic influencing factors (including landslides and seismic impacts) for different railway structures. Afterward, a 3-D environmental suitability map can be generated using a multi-criteria decision-making approach to combine the considered factors. The map is further integrated into the alignment optimization process based on a 3-D distance transform algorithm. The proposed model and method are applied to two complex realistic railway cases. The results demonstrate that they can considerably improve the search efficiency and also find better alignments compared to the best alternatives obtained manually by experienced human designers and produced by a previous distance transform algorithm as well as a genetic algorithm.\",\"PeriodicalId\":50358,\"journal\":{\"name\":\"Integrated Computer-Aided Engineering\",\"volume\":\"67 1\",\"pages\":\"67-88\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2022-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Integrated Computer-Aided Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.3233/ica-220692\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrated Computer-Aided Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3233/ica-220692","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 2

摘要

铁路线路设计是一个受复杂环境因素影响的复杂问题。虽然已经提出了许多路线优化方法,但它们的普遍局限性是缺乏空间环境适宜性分析来指导后续的路线搜索。因此,在研究区域中仍有许多不利区域需要搜索,这大大降低了优化效率。为解决这一问题,提出了铁路环境适宜性评价的地理信息模型。首先将研究区域抽象为空间体素集,确定铁路的三维可达范围。然后,设计了考虑地形影响因素(包括影响结构成本和稳定性的因素)和地质影响因素(包括滑坡和地震影响)的不同铁路结构的地理信息模型。然后,使用多准则决策方法将考虑的因素组合在一起,生成三维环境适宜性图。将该地图进一步集成到基于三维距离变换算法的对齐优化过程中。将所提出的模型和方法应用于两个复杂的实际铁路实例。结果表明,与经验丰富的人类设计师手动获得的最佳替代方案和以前的距离变换算法以及遗传算法产生的最佳替代方案相比,它们可以显着提高搜索效率,并找到更好的对齐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A geographic information model for 3-D environmental suitability analysis in railway alignment optimization
Railway alignment design is a complicated problem affected by intricate environmental factors. Although numerous alignment optimization methods have been proposed, a general limitation among them is the lack of a spatial environmental suitability analysis to guide the subsequent alignment search. Consequently, many unfavorable regions in the study area are still searched, which significantly degrades optimization efficiency. To solve this problem, a geographic information model is proposed for evaluating the environmental suitability of railways. Initially, the study area is abstracted as a spatial voxel set and the 3-D reachable ranges of railways are determined. Then, a geographic information model is devised which considers topographic influencing factors (including those affecting structural cost and stability) as well as geologic influencing factors (including landslides and seismic impacts) for different railway structures. Afterward, a 3-D environmental suitability map can be generated using a multi-criteria decision-making approach to combine the considered factors. The map is further integrated into the alignment optimization process based on a 3-D distance transform algorithm. The proposed model and method are applied to two complex realistic railway cases. The results demonstrate that they can considerably improve the search efficiency and also find better alignments compared to the best alternatives obtained manually by experienced human designers and produced by a previous distance transform algorithm as well as a genetic algorithm.
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
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
×
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