A Markov Chain Approach on Daily Rainfall Occurrence ijtsrd


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.

by 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,

URL: https://www.ijtsrd.com/papers/ijtsrd28075.pdf

Paper URL: https://www.ijtsrd.com/computer-science/data-miining/28075/a-markov-chain-approach-on-daily-rainfall-occurrence/phyu-thwe

call for paper Geological Engineering, international journal Real-time Computing, ugc approved journals Telecommunications




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