基于GPT3模式和随机森林的中国大陆天顶对流层延迟模型

IF 4.5 1区地球科学 Q1 REMOTE SENSING

GPS Solutions Pub Date : 2023-07-15 DOI:10.1007/s10291-023-01513-6

Junyu Li, Qinglan Zhang, Lilong Liu, Yibin Yao, Liangke Huang, Fade Chen, Lv Zhou, Bao Zhang

引用次数: 2

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A refined zenith tropospheric delay model for Mainland China based on the global pressure and temperature 3 (GPT3) model and random forest

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来源期刊

GPS Solutions 工程技术-遥感

CiteScore

8.10

自引率

12.20%

发文量

138

审稿时长

3.1 months

期刊介绍： GPS Solutions is a scientific journal. It is published quarterly and features system design issues and a full range of current and emerging applications of global navigation satellite systems (GNSS) such as GPS, GLONASS, Galileo, BeiDou, local systems, and augmentations. Novel, innovative, or highly demanding uses are of prime interest. Areas of application include: aviation, surveying and mapping, forestry and agriculture, maritime and waterway navigation, public transportation, time and frequency comparisons and dissemination, space and satellite operations, law enforcement and public safety, communications, meteorology and atmospheric science, geosciences, monitoring global change, technology and engineering, GIS, geodesy, and others. GPS Solutions addresses the latest developments in GNSS infrastructure, mathematical modeling, algorithmic developments and data analysis, user hardware, and general issues that impact the user community. Contributions from the entire spectrum of GNSS professionals are represented, including university researchers, scientists from government laboratories, receiver industry and other commercial developers, public officials, and business leaders.