Abstract
Since the tropospheric delay plays a crucial role in meteorological studies and weather forecasts as well as positioning accuracy, accurate prediction of its value is critical to helping monitoring the ZTD variation on a global basis. In the previous chapter, ZTD has been estimated with a fuzzy inference system that uses a back-propagation algorithm. The input of the system is surface meteorological data and the test output is ZTD from GPS. For a test case, a combination of surface pressure (P), temperature (T), or relative humidity (H) is performed to obtain the best estimation of ZTD model. Based on the prospect of ZTD estimation using ANFIS, this chapter will focus on how to predict ZTD value using the surface meteorological data.
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References
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Suparta, W., Alhasa, K.M. (2016). Prediction of ZTD Based on ANFIS Model. In: Modeling of Tropospheric Delays Using ANFIS. SpringerBriefs in Meteorology. Springer, Cham. https://doi.org/10.1007/978-3-319-28437-8_5
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DOI: https://doi.org/10.1007/978-3-319-28437-8_5
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