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Estimation of Atmospheric Water Vapor from ANFIS Technique and Its Validation with GPS Data
Copyright policy )LPPM Institut Teknologi Telkom PurwokertoEstimation of Atmospheric Water Vapor from ANFIS Technique and Its Validation with GPS Data
Adaptive neuro-fuzzy inference system (ANFIS) is a prospective approach in modeling weather parameters based on learning from historical data used. This study presented the comparison of tropospheric precipitable water vapor (PWV) between ANFIS and Global Positioning System (GPS) for areas in Pekan, Pahang, Malaysia. The PWV value was estimated with the ANFIS model with the surface meteorological data as inputs. The accuracy of PWV from ANFIS has been validated with PWV from GPS measurements for the period of 2010. The result showed that the ANFIS PWV has a similar trend with the GPS PWV (r = 0.999 at the 99% confidence level) and found a difference of 0.024%. The PWV from ANFIS was calculated 0.035% higher compared to GPS PWV and found a similar character in two seasonal monsoons. This indicates that the PWV obtained with ANFIS model agreed very well with GPS measurements and it can be implemented to monitor atmospheric variability as well as climate change studies in the absence of GPS data
- National University of Malaysia Malaysia
Microsoft Academic Graph classification: Adaptive neuro fuzzy inference system Gps data Inference system Global Positioning System business.industry business Environmental science Precipitable water vapor Meteorology Atmospheric water Troposphere
Library of Congress Subject Headings: lcsh:Telecommunication lcsh:TK5101-6720
Microsoft Academic Graph classification: Adaptive neuro fuzzy inference system Gps data Inference system Global Positioning System business.industry business Environmental science Precipitable water vapor Meteorology Atmospheric water Troposphere
Library of Congress Subject Headings: lcsh:Telecommunication lcsh:TK5101-6720
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- National University of Malaysia Malaysia
Adaptive neuro-fuzzy inference system (ANFIS) is a prospective approach in modeling weather parameters based on learning from historical data used. This study presented the comparison of tropospheric precipitable water vapor (PWV) between ANFIS and Global Positioning System (GPS) for areas in Pekan, Pahang, Malaysia. The PWV value was estimated with the ANFIS model with the surface meteorological data as inputs. The accuracy of PWV from ANFIS has been validated with PWV from GPS measurements for the period of 2010. The result showed that the ANFIS PWV has a similar trend with the GPS PWV (r = 0.999 at the 99% confidence level) and found a difference of 0.024%. The PWV from ANFIS was calculated 0.035% higher compared to GPS PWV and found a similar character in two seasonal monsoons. This indicates that the PWV obtained with ANFIS model agreed very well with GPS measurements and it can be implemented to monitor atmospheric variability as well as climate change studies in the absence of GPS data