Modeling of Tropospheric Delays Using ANFIS
Nonfiction, Science & Nature, Science, Other Sciences, Meteorology, Computers, Internet
| Author: | Wayan Suparta, Kemal Maulana Alhasa | ISBN: | 9783319284378 |
| Publisher: | Springer International Publishing | Publication: | December 22, 2015 |
| Imprint: | Springer | Language: | English |
| Author: | Wayan Suparta, Kemal Maulana Alhasa |
| ISBN: | 9783319284378 |
| Publisher: | Springer International Publishing |
| Publication: | December 22, 2015 |
| Imprint: | Springer |
| Language: | English |
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.
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.
