Thitipong Kanchai, Nahatai Tepkasetkul, Tippatai Pongsart, Watcharin Klongdee, "Rainfall Data Fitting based on An Improved Mixture Cosine Model with Markov Chain," WSEAS Transactions on Information Science and Applications, vol. 20, pp. 28-33, 2023, DOI:10.37394/23209.2023.20.4
Thitipong Kanchai, Nahatai Tepkasetkul, Tippatai Pongsart, Watcharin Klongdee. Rainfall Data Fitting based on An Improved Mixture Cosine Model with Markov Chain.
WSEAS Transactions on Information Science and Applications. 2023;20:28-33. 10.37394/23209.2023.20.4
WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 20, 2023
Rainfall Data Fitting based on An Improved Mixture Cosine Model with Markov Chain
Authors: , , ,
Abstract: This article proposes a model that uses the adjusted mixture cosine model of two components with Markov chain $$(MC_{2}MC)$$ for predicting the monthly rainfall with actual data from Khon Kaen meteorological station (381201) in Khon Kaen province, Thailand. The data considers 31 years of historical data from January 1991 to December 2021. The evaluation is measured by the root mean square error (RMSE) and the $$R^2$$ values. We found that the mixture cosine model has RMSE and $$R^2$$ values of 70.72 and 52.49%, respectively, and the $$(MC_{2}MC)$$ model has RMSE and $$R^2$$ values of 42.43 and 82.53%, respectively.
Pages: 28-33 WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 20, 2023, Art. #4 DOI: 10.37394/23209.2023.20.4
×
Citation Tools