基于加权马尔可夫链的砀山地区降水预测

Proceedings of the International Conference on High Performance Compilation, Computing and Communications Pub Date : 2017-03-22 DOI:10.1145/3069593.3069617

Yiqi Gui, Jun Shao

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引用次数: 7

摘要

本文的目的是利用加权马尔可夫链和模糊集理论对砀山降水进行预测。以砀山1961—2015年的年降水量为基础，应用加权马尔可夫链对2011—2015年的年降水量进行了预测。结果表明，该模型具有较高的预测精度，为预测砀山地区年降水量提供了一条值得探索的途径。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Prediction of Precipitation Based on Weighted Markov Chain in Dangshan

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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Proceedings of the International Conference on High Performance Compilation, Computing and Communications

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