research-article

Prediction of Precipitation Based on Weighted Markov Chain in Dangshan

Authors:

Yiqi Gui,

Jun ShaoAuthors Info & Claims

HP3C-2017: Proceedings of the International Conference on High Performance Compilation, Computing and Communications

Pages 81 - 85

https://doi.org/10.1145/3069593.3069617

Published: 22 March 2017 Publication History

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Abstract

The purpose of this paper is to predict the precipitation in Dangshan using the weighted Markov chain and fuzzy set theory. Based on annual precipitation in Dangshan during 1961-2015, we apply the weighted Markov chain to predict the annual precipitation from 2011--2015. The results show that our proposed model has high prediction accuracy which provides a way worth of exploration for predicting annual precipitation in Dangshan.

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Cited By

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Liu ZZhou JYang XZhao ZLv Y(2024)Research on Water Resource Modeling Based on Machine Learning TechnologiesWater10.3390/w1603047216:3(472)Online publication date: 31-Jan-2024
https://doi.org/10.3390/w16030472
Yang LChen CGuo RBi CLi YQiu X(2024)D-Markov: A Sparse Sample-based Model for Interannual Precipitation Prediction during the Rainy SeasonProceedings of the 17th International Symposium on Visual Information Communication and Interaction10.1145/3678698.3678711(1-8)Online publication date: 11-Dec-2024
https://dl.acm.org/doi/10.1145/3678698.3678711
Hajani ESarma G(2023)Generation of rainfall data series by using the Markov Chain model in three selected sites in the Kurdistan Region, IraqAI in Civil Engineering10.1007/s43503-023-00014-22:1Online publication date: 7-Jun-2023
https://doi.org/10.1007/s43503-023-00014-2
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Published In

HP3C-2017: Proceedings of the International Conference on High Performance Compilation, Computing and Communications

March 2017

149 pages

ISBN:9781450348683

DOI:10.1145/3069593

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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UTM: Universiti Teknologi Malaysia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2017

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Funding Sources

National Science Foundation of the jiangsu Province
National Natural Science Foundation of China

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HP3C-2017

HP3C-2017: International Conference on High Performance Compilation, Computing and Communications

March 22 - 24, 2017

Kuala Lumpur, Malaysia

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Cited By

View all

Liu ZZhou JYang XZhao ZLv Y(2024)Research on Water Resource Modeling Based on Machine Learning TechnologiesWater10.3390/w1603047216:3(472)Online publication date: 31-Jan-2024
https://doi.org/10.3390/w16030472
Yang LChen CGuo RBi CLi YQiu X(2024)D-Markov: A Sparse Sample-based Model for Interannual Precipitation Prediction during the Rainy SeasonProceedings of the 17th International Symposium on Visual Information Communication and Interaction10.1145/3678698.3678711(1-8)Online publication date: 11-Dec-2024
https://dl.acm.org/doi/10.1145/3678698.3678711
Hajani ESarma G(2023)Generation of rainfall data series by using the Markov Chain model in three selected sites in the Kurdistan Region, IraqAI in Civil Engineering10.1007/s43503-023-00014-22:1Online publication date: 7-Jun-2023
https://doi.org/10.1007/s43503-023-00014-2
Ali ZHussain INazeer AFaisal MIsmail MQamar SGrzegorczyk MZahid FNi G(2020)Measuring and restructuring the risk in forecasting drought classes: an application of weighted Markov chain based model for standardised precipitation evapotranspiration index (SPEI) at one-month time scaleTellus A: Dynamic Meteorology and Oceanography10.1080/16000870.2020.184020972:1(1840209)Online publication date: 1-Jan-2020
https://doi.org/10.1080/16000870.2020.1840209
Ali ZHussain IFaisal MKhan DNiaz RElashkar EShoukry A(2020)Propagation of the Multi-Scalar Aggregative Standardized Precipitation Temperature Index and its ApplicationWater Resources Management10.1007/s11269-019-02469-434:2(699-714)Online publication date: 6-Jan-2020
https://doi.org/10.1007/s11269-019-02469-4
Ali ZHussain IFaisal MShoukry AGani SAhmad I(2019)A framework to identify homogeneous drought characterization regionsTheoretical and Applied Climatology10.1007/s00704-019-02797-w137:3-4(3161-3172)Online publication date: 12-Feb-2019
https://doi.org/10.1007/s00704-019-02797-w
Zarei A(2018)Evaluation of Drought Condition in Arid and Semi- Arid Regions, Using RDI IndexWater Resources Management10.1007/s11269-017-1898-932:5(1689-1711)Online publication date: 5-Jan-2018
https://doi.org/10.1007/s11269-017-1898-9

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