Overview
- Describes a new technique to obtain ZTD value to retrieve water vapor for improving weather forecasting by meteorologist and researchers
- Beneficial for graduate students and young researchers involved with GPS applications
- Can be used by lecturers at university level for courses such as Artificial Intelligence, Applied GIS & GPS, Statistics and Forecasting
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Meteorology (BRIEFSMETEOR)
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Table of contents (5 chapters)
Keywords
About this book
This book investigates tropospheric delays, one of the main error sources in Global Navigation Satellite Systems (GNSS), and its impact plays a crucial role in near real-time weather forecasting. Accessibility and accurate estimation of this parameter are essential for weather and climate research. Advances in GNNS application has allowed the measurements of Zenith Tropospheric Delay (ZTD) in all weather conditions and on a global scale with fine temporal and spatial resolution. However, GPS data are not always available for a full 24-hour period. Using a soft computing technique such as Adaptive Neuro-Fuzzy Inference System (ANFIS) as a new alternative, the ZTD can be determined by using the surface meteorological data as inputs. The estimation and prediction of ZTD value are presented in this book.
Authors and Affiliations
Bibliographic Information
Book Title: Modeling of Tropospheric Delays Using ANFIS
Authors: Wayan Suparta, Kemal Maulana Alhasa
Series Title: SpringerBriefs in Meteorology
DOI: https://doi.org/10.1007/978-3-319-28437-8
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: The Author(s) 2016
Softcover ISBN: 978-3-319-28435-4Published: 29 January 2016
eBook ISBN: 978-3-319-28437-8Published: 22 December 2015
Series ISSN: 2199-9112
Series E-ISSN: 2199-9120
Edition Number: 1
Number of Pages: XVI, 109
Number of Illustrations: 28 b/w illustrations, 23 illustrations in colour
Topics: Atmospheric Sciences, Meteorology, Models and Principles, Complex Systems, Statistical Physics and Dynamical Systems