Estimation of precipitable water vapor using an adaptive neuro-fuzzy inference system technique

Wayan Suparta, Kemal Maulana Alhasa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Water vapor has an important role in the global climate change development. Because it is essential to human life, many researchers proposed the estimation of atmospheric water vapor values such as for meteorological applications. Lacking of water vapor data in a certain area will a problem in the prediction of current climate change. Here, we reported a novel precipitable water vapor (PWV) estimation using an adaptive neuro-fuzzy inference system (ANFIS) model that has powerful accuracy and higher level. Observation of the surface temperature, barometric pressure and relative humidity from 4 to 10 April 2011 has been used as training and the PWV derived from GPS as a testing of these models. The results showed that the model has demonstrated its ability to learn well in events that are trained to recognize. It has been found a good skill in estimating the PWV value, where strongest correlation was observed for UMSK station (r = 0.95) and the modest correlation was for NTUS station (r = 0.73). In general, the resulting error is very small (less than 5%). Thus, this model approach can be proposed as an alternative method in estimating the value of PWV for the location where the GPS data is inaccessible.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages214-222
Number of pages9
Volume7804 LNCS
DOIs
Publication statusPublished - 2013
EventInternational Conference on Information and Communication Technology, ICT-EurAsia 2013 - Yogyakarta
Duration: 25 Mar 201329 Mar 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7804 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Conference on Information and Communication Technology, ICT-EurAsia 2013
CityYogyakarta
Period25/3/1329/3/13

Fingerprint

Adaptive Neuro-fuzzy Inference System
Water Vapor
Fuzzy inference
Water vapor
Climate Change
Climate change
Global positioning system
Relative Humidity
Model
Atmospheric humidity
Testing
Prediction
Alternatives

Keywords

  • Adaptive neuro-fuzzy inference system
  • Estimation
  • Meteorological applications
  • PWV

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Suparta, W., & Alhasa, K. M. (2013). Estimation of precipitable water vapor using an adaptive neuro-fuzzy inference system technique. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7804 LNCS, pp. 214-222). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7804 LNCS). https://doi.org/10.1007/978-3-642-36818-9_22

Estimation of precipitable water vapor using an adaptive neuro-fuzzy inference system technique. / Suparta, Wayan; Alhasa, Kemal Maulana.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7804 LNCS 2013. p. 214-222 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7804 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suparta, W & Alhasa, KM 2013, Estimation of precipitable water vapor using an adaptive neuro-fuzzy inference system technique. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7804 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7804 LNCS, pp. 214-222, International Conference on Information and Communication Technology, ICT-EurAsia 2013, Yogyakarta, 25/3/13. https://doi.org/10.1007/978-3-642-36818-9_22
Suparta W, Alhasa KM. Estimation of precipitable water vapor using an adaptive neuro-fuzzy inference system technique. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7804 LNCS. 2013. p. 214-222. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-36818-9_22
Suparta, Wayan ; Alhasa, Kemal Maulana. / Estimation of precipitable water vapor using an adaptive neuro-fuzzy inference system technique. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7804 LNCS 2013. pp. 214-222 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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