云平台下基于半朴素贝叶斯的降雨量预测

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (5): 1117-1123.

云平台下基于半朴素贝叶斯的降雨量预测

薛胜军^1,2, 张佩云¹, 陈静怡¹

1.南京信息工程大学计算机与软件学院,南京 210044;
2.南京信息工程大学江苏省网络监控中心,南京 210044

收稿日期:2014-12-28 修回日期:2015-03-13 发布日期:2020-07-03
作者简介:薛胜军(1976-),男,山东青岛,博士后,教授,博导,研究方向为计算机网络、云计算、应用气象。
基金资助:
国家自然科学基金(41275116),江苏省经济和信息化委员会项目({2011}1178)

Semi-naive Bayesian Forecasts Rainfall on Cloud Platform

Xue Shengjun^1,2, Zhang Peiyun¹, Chen Jingyi¹

1. School of Computer and Software, Nanjing University of Information science and Technology, Nanjing 210044, China;
2. Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information and Technology, Nanjing 210044, China

Received:2014-12-28 Revised:2015-03-13 Published:2020-07-03

摘要/Abstract

摘要： 随着降雨量预测在中国的气象预报行业中日趋重要,降雨量预测的方法也越来越多。由于云平台可以有效地提高预测的效率和准确率,云平台也逐渐被应用到气象行业。目前我们运用的降雨量预测方法要求属性之间独立,但是很多气象要素之间并不独立,这就降低了预测的准确性。因此,结合并利用模糊集理论的相关知识,提出了一个基于云平台的半朴素贝叶斯预测降雨量的方法。为证明预测的准确性和高效性,建立了一个预测模型,用气象站提供的气象数据预测下个月的降雨量。实验结果证明,建立的模型与先前的模型相比,具有更高的预测准确性和效率。

关键词: 云平台, 降雨量预测, 模糊集理论, 半朴素贝叶斯

Abstract: Rainfall forecast has played an increasingly important role of meteorological services. As cloud platform can improve the efficiency and accuracy of rainfall forecast, it has been applied to forecast rainfall. The recent forecast methods require the independence between all the attributes, but most of the meteorological factors are interdependent, which reduces the accuracy of the prediction. Consequently, a semi-naive Bayesian classification was proposed combined with fuzzy set theory realizing it on cloud platform. At the same time, to improve the accuracy and the efficiency of rainfall forecast, a forecast model was established, which used the historical weather data provided by the weather stations to forecast the next-month rainfall. The experimental results show the method is able to provide higher accuracy and efficiency of rainfall forecast compared with the previous methods.

Key words: cloud platform, rainfall forecast, fuzzy sets theory, Semi-Naive Bayesian

中图分类号:

TP311.13

薛胜军, 张佩云, 陈静怡. 云平台下基于半朴素贝叶斯的降雨量预测[J]. 系统仿真学报, 2016, 28(5): 1117-1123.

Xue Shengjun, Zhang Peiyun, Chen Jingyi. Semi-naive Bayesian Forecasts Rainfall on Cloud Platform[J]. Journal of System Simulation, 2016, 28(5): 1117-1123.

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