Rainfall Forecasting Using Bayesian Nonparametric Regression

Annas, Suwardi and Arisandi, R (2016) Rainfall Forecasting Using Bayesian Nonparametric Regression. In: 3rd INTERNATIONAL CONFERENCE ON RESEARCH, IMPLEMENTATION AND EDUCATION OF MATHEMATICS AND SCIENCE (3rd ICRIEMS), 16-17 Mei 2016, Yogyakarta, Indonesia.

[img] Text (Artikel Prosiding Internasional)
Artikel Prosiding Internasional - Rainfall Forecasting Using Bayesian.pdf - Published Version

Download (270kB)
[img] Text (Peer Review Artikel Prosiding Internasional)
Peer Review Artikel Prosiding Internasional - Rainfall Forecasting Using Bayesian.pdf - Published Version

Download (942kB)
[img] Text (Turnitin Artikel Prosiding Internasional)
Turnitin Artikel Prosiding Internasional - Rainfall forecasting.pdf - Published Version

Download (1MB)
Official URL: http://seminar.uny.ac.id/icriems/proceedings2016

Abstract

In the present years, climate change due to global warming, resulting in the change of seasons in Indonesia is high variability and unpredictable. Many methods that can be used to predict rainfall pattern, such as parametric regression and ARIMA. However, the model obtained through parametrics statistical approach only concerned to information of samples, therefore, it is poor to interpret the parameters of the rainfall pattern. This study proposes a bayesian nonparametric regression with Gaussian Regression Process approach for rainfall forecasting in the City of Makassar, Indonesia. Based on the value of Root Mean Square Error Prediction (RMSEP), the best covariance function that can be used to forecast is quadratic exponential.

Item Type: Conference or Workshop Item (Paper)
Subjects: KARYA ILMIAH DOSEN
Universitas Negeri Makassar > KARYA ILMIAH DOSEN
Divisions: KOLEKSI KARYA ILMIAH UPT PERPUSTAKAAN UNM MENURUT FAKULTAS > KARYA ILMIAH DOSEN
KARYA ILMIAH DOSEN
Depositing User: S.T., M.T. Faruq Ratuhaji
Date Deposited: 31 Dec 2020 00:43
Last Modified: 31 Dec 2020 00:45
URI: http://eprints.unm.ac.id/id/eprint/18863

Actions (login required)

View Item View Item