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A Markov Chain Approach on Daily Rainfall Occurrence

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A Markov Chain Approach on Daily Rainfall Occurrence


Phyu Thwe | Ei Khaing Win | Hnin Pwint Myu Wai



Phyu Thwe | Ei Khaing Win | Hnin Pwint Myu Wai "A Markov Chain Approach on Daily Rainfall Occurrence" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6, October 2019, pp.280-282, URL: https://www.ijtsrd.com/papers/ijtsrd28075.pdf

Markov modeling is one of the tools that can be used to help planners for assess precipitation. The first order Markov chain model was used to predict daily precipitation intervals using transition probability matrices. The demand for precipitation is increasing, not only for data invention, but also to provide useful information in numerous applications, including water properties organization and the hydrological and agricultural subdivisions. In this study, the objective is to predict the probability of future precipitation of the city of Pyin Oo Lwin using the Markov chain model. The system was developed on the basis of the Markov method to forecast the occurrence of precipitation. The results show that models can forecast the state of a given day by 74% on average.

prediction, markov chain, precipitation


IJTSRD28075
Volume-3 | Issue-6, October 2019
280-282
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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