用改进的灰狼法优化等级不足的全球导航卫星系统网络的 L1 准则

IF 1.2 4区 地球科学 Q3 ENGINEERING, CIVIL Survey Review Pub Date : 2024-03-12 DOI:10.1080/00396265.2024.2327124
V. Mahboub, S. Ebrahimzadeh, A. Baghani, A. Rastegar, M. Zanganeh
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引用次数: 0

摘要

由于标准灰狼优化(GWO)算法和全局优化(GO)算法都是在GNSS网络中直接进行L1正则优化以检测异常值,因此提出了一种改进的灰狼优化(GWO)算法。
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L1-norm optimisation of rank deficient GNSS networks by an improved Grey Wolf method
An improved grey wolf optimization (GWO) is proposed for direct L1-norm optimization in rank deficient GNSS networks to detect outliers since the standard GWO and the global optimization (GO) algor...
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来源期刊
Survey Review
Survey Review 地学-地球科学综合
CiteScore
3.50
自引率
6.20%
发文量
33
审稿时长
6 months
期刊介绍: Survey Review is an international journal that has been published since 1931, until recently under the auspices of the Commonwealth Association of Surveying and Land Economy (CASLE). The journal is now published for Survey Review Ltd and brings together research, theory and practice of positioning and measurement, engineering surveying, cadastre and land management, and spatial information management. All papers are peer reviewed and are drawn from an international community, including government, private industry and academia. Survey Review is invaluable to practitioners, academics, researchers and students who are anxious to maintain their currency of knowledge in a rapidly developing field.
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