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010   $a3-319-28437-1
024 7 $a10.1007/978-3-319-28437-8
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035   $a(PQKBTitleCode)TC0001597115
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035   $a(DE-He213)978-3-319-28437-8
035   $a(MiAaPQ)EBC4201223
035   $a(PPN)190884231
035   $a(EXLCZ)993710000000541819
100   $a20151222d2016      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aModeling of Tropospheric Delays Using ANFIS /$fby Wayan Suparta, Kemal Maulana Alhasa
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (124 p.)
225 1 $aSpringerBriefs in Meteorology,$x2199-9112
300   $aDescription based upon print version of record.
311 08$a3-319-28435-5 
320   $aIncludes bibliographical references and index.
327   $aIntroduction -- Adaptive Neuro Fuzzy Inference System -- Tropospheric Delay Modeling from GPS -- Estimation of ZTD Using ANFIS -- Prediction of ZTD Based on ANFIS Model.
330   $aThis book investigates tropospheric delays, one of the main error sources in Global Navigation Satellite Systems (GNSS), and its impact plays a crucial role in near real-time weather forecasting. Accessibility and accurate estimation of this parameter are essential for weather and climate research. Advances in GNNS application has allowed the measurements of Zenith Tropospheric Delay (ZTD) in all weather conditions and on a global scale with fine temporal and spatial resolution. However, GPS data are not always available for a full 24-hour period. Using a soft computing technique such as Adaptive Neuro-Fuzzy Inference System (ANFIS) as a new alternative, the ZTD can be determined by using the surface meteorological data as inputs. The estimation and prediction of ZTD value are presented in this book.
410  0$aSpringerBriefs in Meteorology,$x2199-9112
606   $aAtmospheric science
606   $aMeteorology
606   $aComputers
606   $aStatistical physics
606   $aDynamics
606   $aAtmospheric Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/G36000
606   $aMeteorology$3https://scigraph.springernature.com/ontologies/product-market-codes/312000
606   $aModels and Principles$3https://scigraph.springernature.com/ontologies/product-market-codes/I18016
606   $aComplex Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/P33000
606   $aStatistical Physics and Dynamical Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/P19090
615  0$aAtmospheric science.
615  0$aMeteorology.
615  0$aComputers.
615  0$aStatistical physics.
615  0$aDynamics.
615 14$aAtmospheric Sciences.
615 24$aMeteorology.
615 24$aModels and Principles.
615 24$aComplex Systems.
615 24$aStatistical Physics and Dynamical Systems.
676   $a550
700   $aSuparta$b Wayan$4aut$4http://id.loc.gov/vocabulary/relators/aut$01062783
702   $aAlhasa$b Kemal Maulana$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254108003321
996   $aModeling of Tropospheric Delays Using ANFIS$92528553
997   $aUNINA