水生不会飞的鸟能分配汽车安全要求吗?

Y. Gheraibia, A. Moussaoui, Luís Silva Azevedo, D. Parker, Y. Papadopoulos, M. Walker
{"title":"水生不会飞的鸟能分配汽车安全要求吗?","authors":"Y. Gheraibia, A. Moussaoui, Luís Silva Azevedo, D. Parker, Y. Papadopoulos, M. Walker","doi":"10.1109/INTELCIS.2015.7397214","DOIUrl":null,"url":null,"abstract":"Many emerging safety standards use the concept of Safety Integrity Levels (SILs) for guiding designers on how to specify system safety requirements and then allocate these requirements to elements of the system architecture. These standards include the new automotive safety standard ISO 26262 in which SILs are called automotive SILs (or ASILs) and these will be used to illustrate the application of the techniques presented in this paper. In this paper, we propose a new approach in which the allocation of ASILs is performed by a new nature-inspired metaheuristic known as Penguins Search Optimisation Algorithm (PeSOA). PeSOA mimics the collaborative hunting strategy of penguins, using the metaphor of oxygen reserves as a search intensification operator. This allows the penguins to preserve energy, consuming it only in areas of the search space that are rich in good solutions. The performance of the approach is evaluated by applying it to a benchmark hybrid braking system case study, demonstrating performance that is an improvement to those reported in the literature.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"157 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Can aquatic flightless birds allocate Automotive Safety requirements?\",\"authors\":\"Y. Gheraibia, A. Moussaoui, Luís Silva Azevedo, D. Parker, Y. Papadopoulos, M. Walker\",\"doi\":\"10.1109/INTELCIS.2015.7397214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many emerging safety standards use the concept of Safety Integrity Levels (SILs) for guiding designers on how to specify system safety requirements and then allocate these requirements to elements of the system architecture. These standards include the new automotive safety standard ISO 26262 in which SILs are called automotive SILs (or ASILs) and these will be used to illustrate the application of the techniques presented in this paper. In this paper, we propose a new approach in which the allocation of ASILs is performed by a new nature-inspired metaheuristic known as Penguins Search Optimisation Algorithm (PeSOA). PeSOA mimics the collaborative hunting strategy of penguins, using the metaphor of oxygen reserves as a search intensification operator. This allows the penguins to preserve energy, consuming it only in areas of the search space that are rich in good solutions. The performance of the approach is evaluated by applying it to a benchmark hybrid braking system case study, demonstrating performance that is an improvement to those reported in the literature.\",\"PeriodicalId\":6478,\"journal\":{\"name\":\"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)\",\"volume\":\"157 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INTELCIS.2015.7397214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2015.7397214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

许多新兴的安全标准使用安全完整性等级(SILs)的概念来指导设计者如何指定系统安全需求,然后将这些需求分配给系统架构的元素。这些标准包括新的汽车安全标准ISO 26262,其中sil被称为汽车sil(或asil),这些标准将用于说明本文中介绍的技术的应用。在本文中,我们提出了一种新的方法,其中ASILs的分配由一种新的自然启发的元启发式算法执行,称为企鹅搜索优化算法(PeSOA)。PeSOA模仿企鹅的合作狩猎策略,使用氧气储备作为搜索强化算子的隐喻。这使得企鹅可以保存能量,只在搜索空间中有丰富的好的解决方案的区域消耗能量。通过将该方法应用于基准混合动力制动系统案例研究来评估该方法的性能,证明其性能比文献中报道的性能有所改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Can aquatic flightless birds allocate Automotive Safety requirements?
Many emerging safety standards use the concept of Safety Integrity Levels (SILs) for guiding designers on how to specify system safety requirements and then allocate these requirements to elements of the system architecture. These standards include the new automotive safety standard ISO 26262 in which SILs are called automotive SILs (or ASILs) and these will be used to illustrate the application of the techniques presented in this paper. In this paper, we propose a new approach in which the allocation of ASILs is performed by a new nature-inspired metaheuristic known as Penguins Search Optimisation Algorithm (PeSOA). PeSOA mimics the collaborative hunting strategy of penguins, using the metaphor of oxygen reserves as a search intensification operator. This allows the penguins to preserve energy, consuming it only in areas of the search space that are rich in good solutions. The performance of the approach is evaluated by applying it to a benchmark hybrid braking system case study, demonstrating performance that is an improvement to those reported in the literature.
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