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[1]陈增强,高艺博,陈成功,等.基于改进型萤火虫群优化算法泄漏源源强及位置反算研究*[J].中国安全生产科学技术,2022,18(10):150-155.[doi:10.11731/j.issn.1673-193x.2022.10.022]
 CHEN Zengqiang,GAO Yibo,CHEN Chenggong,et al.Study on inverse calculation of leakage source intensity and location based on improved glowworm swarm optimization algorithms[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(10):150-155.[doi:10.11731/j.issn.1673-193x.2022.10.022]
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基于改进型萤火虫群优化算法泄漏源源强及位置反算研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
18
期数:
2022年10期
页码:
150-155
栏目:
职业安全卫生管理与技术
出版日期:
2022-10-31

文章信息/Info

Title:
Study on inverse calculation of leakage source intensity and location based on improved glowworm swarm optimization algorithms
文章编号:
1673-193X(2022)-10-0150-06
作者:
陈增强高艺博陈成功汪艺萌
(北京石油化工学院 信息工程学院,北京 102617)
Author(s):
CHEN Zengqiang GAO Yibo CHEN Chenggong WANG Yimeng
(School of Information Engineering,Beijing Institute of Petrochemical Technology,Beijing 102617,China)
关键词:
萤火虫群优化算法Nelder Mead单纯形算法泄漏源定位源强反算混合策略
Keywords:
glowworm swarm optimization algorithm Nelder Mead simplex algorithm leakage source location inverse calculation of source intensity hybrid strategy
分类号:
X937
DOI:
10.11731/j.issn.1673-193x.2022.10.022
文献标志码:
A
摘要:
针对标准萤火虫群优化算法(GSO)在危化品泄漏源源强及位置反算中存在精度不高,容易陷入局部最优等局限,提出混合萤火虫-Nelder Mead单纯形算法(GSO-NM),并与基于步长的改进萤火虫群优化算法(MGSO)以及单纯形搜索混合协同进化萤火虫群优化算法(HCGSOSSM)进行比较分析,将3种改进型萤火虫群优化算法应用于泄漏源源强及位置反算中进行比较分析。研究结果表明:GSO-NM算法可以有效提高定位精度和稳定性,能较为精确地反算出泄漏源源强及位置,为泄漏源源强及位置反算研究提供1种新思路。
Abstract:
In view of the limitations of standard glowworm swarm optimization (GSO) algorithm,such as low accuracy and easy to fall into local optimization,in the inverse calculation of leakage source intensity and location of hazardous chemicals,a hybrid glowworm swarm optimization and Nelder Mead simplex algorithm (GSO-NM) was proposed.The GSO-NM algorithm was compared with the improved glowworm swarm optimization algorithm based on step size (MGSO) and the hybrid coevolutionary glowworm swarm optimization algorithm with simplex search method (HCGSOSSM).Three improved glowworm swarm optimization algorithms were applied in the inverse calculation of the leakage source intensity and location.The results showed that the GSO-NM algorithm improved the localization accuracy and stability,and could accurately calculate the source intensity and location of leakage source inversely,which provides a new idea for the research on the inverse calculation of leakage source intensity and location.

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备注/Memo

备注/Memo:
收稿日期: 2022-01-14
* 基金项目: 北京市社科基金项目(16GLC062);北京市教委项目(KM201710017008);北京市自然科学基金项目(9192009);北京石油化工学院交叉科研探索项目(BIPTCSF-011)
作者简介: 陈增强,博士,讲师,主要研究方向为危化品大气扩散模拟及事故源的定位方法。
更新日期/Last Update: 2022-11-13