國立虎尾科技大學 |

Modeling of Tropospheric Delays Using ANFIS

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Modeling of Tropospheric Delays Using ANFIS/ by Wayan Suparta, Kemal Maulana Alhasa.
作者:	Suparta, Wayan.
其他作者:	Alhasa, Kemal Maulana.
面頁冊數:	XVI, 109 p. 51 illus., 23 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Atmospheric sciences. -
電子資源:	https://doi.org/10.1007/978-3-319-28437-8
ISBN:	9783319284378

Modeling of Tropospheric Delays Using ANFIS
Suparta, Wayan.

Modeling of Tropospheric Delays Using ANFIS[electronic resource] /by Wayan Suparta, Kemal Maulana Alhasa. - 1st ed. 2016. - XVI, 109 p. 51 illus., 23 illus. in color.online resource. - SpringerBriefs in Meteorology,2199-9112. - SpringerBriefs in Meteorology,.

Introduction -- Adaptive Neuro Fuzzy Inference System -- Tropospheric Delay Modeling from GPS -- Estimation of ZTD Using ANFIS -- Prediction of ZTD Based on ANFIS Model.

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.

ISBN: 9783319284378

Standard No.: 10.1007/978-3-319-28437-8doiSubjects--Topical Terms:

1179392
Atmospheric sciences.

LC Class. No.: QC851-999

Dewey Class. No.: 551.5

Modeling of Tropospheric Delays Using ANFIS
LDR:02370nam a22003975i 4500 001 974072
003 DE-He213
005 20200706033646.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319284378 $9 978-3-319-28437-8
024 7 $a 10.1007/978-3-319-28437-8 $2 doi
035 $a 978-3-319-28437-8
050 4 $a QC851-999
072 7 $a RB $2 bicssc
072 7 $a SCI042000 $2 bisacsh
072 7 $a RB $2 thema
082 0 4 $a 551.5 $2 23
100 1 $a Suparta, Wayan. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1103906
245 1 0 $a Modeling of Tropospheric Delays Using ANFIS $h [electronic resource] / $c by Wayan Suparta, Kemal Maulana Alhasa.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a XVI, 109 p. 51 illus., 23 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Meteorology, $x 2199-9112
505 0 $a Introduction -- Adaptive Neuro Fuzzy Inference System -- Tropospheric Delay Modeling from GPS -- Estimation of ZTD Using ANFIS -- Prediction of ZTD Based on ANFIS Model.
520 $a 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.
650 0 $a Atmospheric sciences. $3 1179392
650 0 $a Meteorology. $3 554820
650 0 $a Computers. $3 565115
650 0 $a Statistical physics. $3 528048
650 0 $a Dynamical systems. $3 1249739
650 1 4 $a Atmospheric Sciences. $3 881331
650 2 4 $a Models and Principles. $3 669634
650 2 4 $a Complex Systems. $3 888664
650 2 4 $a Statistical Physics and Dynamical Systems. $3 1114011
700 1 $a Alhasa, Kemal Maulana. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1103907
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319284354
776 0 8 $i Printed edition: $z 9783319284361
830 0 $a SpringerBriefs in Meteorology, $x 2199-9112 $3 1266175
856 4 0 $u https://doi.org/10.1007/978-3-319-28437-8
912 $a ZDB-2-EES
912 $a ZDB-2-SXEE
950 $a Earth and Environmental Science (SpringerNature-11646)
950 $a Earth and Environmental Science (R0) (SpringerNature-43711)