利用GEP估算缺失降雨数据:以吉打州Alor Setar Raja河为例

N. Ghani, Z. A. Hasan, T. L. Lau
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引用次数: 5

摘要

水资源和城市洪水管理需要水文和水力建模。然而,在水文模拟过程中,降水数据不完整往往是一个问题。在这项研究中,利用基因表达编程(GEP)将位于马来西亚吉打州Alor Setar的主要气象站的月降水数据与邻近气象站的月降水数据相关联。遗传规划是遗传规划的一种扩展,可以提供简单有效的求解方法。研究说明了GEP在确定代替主雨量站(6103047)的最适宜雨量站中的应用。这是为了确保在主站出现故障时,可以建立一个可靠的雨量站。这些是通过比较主站数据与每个邻近站点的数据来完成的。分析结果表明,38号台站与主台站最相容,R2为0.886。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Missing Rainfall Data Using GEP: Case Study of Raja River, Alor Setar, Kedah
Water resources and urban flood management require hydrologic and hydraulic modeling. However, incomplete precipitation data is often the issue during hydrological modeling exercise. In this study, gene expression programming (GEP) was utilised to correlate monthly precipitation data from a principal station with its neighbouring station located in Alor Setar, Kedah, Malaysia. GEP is an extension to genetic programming (GP), and can provide simple and efficient solution. The study illustrates the applications of GEP to determine the most suitable rainfall station to replace the principal rainfall station (station 6103047). This is to ensure that a reliable rainfall station can be made if the principal station malfunctioned. These were done by comparing principal station data with each individual neighbouring station. Result of the analysis reveals that the station 38 is the most compatible to the principal station where the value of R2 is 0.886.
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