Results 81 to 90 of about 776 (171)

Modeling tropospheric zenith wet delays in the Chinese mainland based on machine learning

, 2023
In this study, the tropospheric zenith wet delay (ZWD) modeling was realized based on the regression analysis of 7 years (2013–2019) of radiosonde data at 182 sites in the Chinese mainland and the surroundings through two machine learning (ML) approaches
Jiang, Zhongshan; orcid:, Yuan, Linguo, Li, Qinzheng   +2 more
core   +1 more source

Quantitative analysis of the tropospheric delay difference using empirical mapping functions on VLBI stations

Frontiers in Astronomy and Space Sciences
Tropospheric delay is a major error source for the high-accuracy Very Long Baseline Interferometry (VLBI) technique due to rapid water vapor variations. The Niell mapping function (NMF) and Global Mapping Function (GMF) are extensively applied to convert
W. L. Zhou, W. L. Zhou, W. L. Zhou, W. L. Zhou, S. L. Song, S. L. Song, J. Jiang, J. Jiang, X. Hu, P. J. Li, P. J. Li, Z. B. Zhang, Z. B. Zhang, Z. B. Zhang   +13 more
doaj   +1 more source

Extending Feature-Based Detection for Artificial Intelligence [PDF]

AI text generation is rapidly developing, and, as a result, it is becoming increasingly difficult to differentiate it from human written text. Our base study by Leon Fröhling et al.
Ahrndt, Kayla
core   +1 more source

Larger Probes Tell a Different Story: Extending Psycholinguistic Datasets Via In-Context Learning [PDF]

, 2023
Language model probing is often used to test specific capabilities of models. However, conclusions from such studies may be limited when the probing benchmarks are small and lack statistical power.
Rumshisky, Anna, Shivagunde, Namrata, Lialin, Vladislav   +2 more
core  

An improved global pressure and zenith wet delay model with optimized vertical correction considering the spatiotemporal variability in multiple height-scale factors [PDF]

Geoscientific Model Development
Atmospheric pressure and zenith wet delay (ZWD) are essential for global navigation satellite system (GNSS) tropospheric correction and precipitable water vapor (PWV) retrieval. As the development progresses of real-time GNSS kinematic technology, moving
C. Jiang, C. Jiang, C. Jiang, X. Gao, H. Zhu, S. Wang, S. Liu, S. Chen, G. Liu   +8 more
doaj   +1 more source

Empirical tropospheric zenith wet delay models with strong generalization capability based on a robust machine learning fusion algorithm

Geodesy and Geodynamics
Tropospheric zenith wet delay (ZWD) plays a vital role in the analysis of space geodetic observations. In recent years, machine learning methods have been increasingly applied to improve the accuracy of ZWD calculations.
Jiahao Zhang, Qin Liang, Yunqing Huang
doaj   +1 more source

Higher accuracy estimation of the weighted mean temperature (tm) with the aid of machine learning and NWP model

All Earth
An accurate calculation of weighted mean temperature (Tm) is highly critical for global navigation satellite system (GNSS) based precipitable water vapour retrieval.
Mingyun Hu, Junyu Li, Chaolong Yao, Feijuan Li, Lilong Liu, Liangke Huang, Yuxin Wang   +6 more
doaj   +1 more source

The ztd estimated values from three models named Site-wise, Grid-wise, and GPT3 and the ztd reference values provided by IGS between 2016 and 2020.

<p>The data includes the zenith total delay (ztd) values computed by three models provided by the VMF data server, namely <strong>Site-wise, Grid-wise, and GPT3</strong>, for target stations during the period from 2016 to 2020, along ...
Yao
core   +1 more source

Selecting ERA5 Grid Spacing for GNSS Tropospheric Parameters over China

Atmosphere
ERA5 is the fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts. It combines observations with a weather model to reconstruct past atmospheric conditions.
Ziyang Ding, Chao Liu, Zihan Peng, Clement Chongo, James Ngoma   +4 more
doaj   +1 more source

Opinerium: Subjective Question Generation Using Large Language Models

IEEE Access
This paper presents a comprehensive study on generating subjective inquiries for news media posts to empower public engagement with trending media topics.
Pedram Babakhani, Andreas Lommatzsch, Torben Brodt, Doreen Sacker, Fikret Sivrikaya, Sahin Albayrak   +5 more
doaj   +1 more source