Water resources and urban flood management require hydrologic and hydraulic modeling. However, incomplete precipitation data\nis often the issue during hydrological modeling exercise. In this study, gene expression programming (GEP) was utilised to correlate\nmonthly precipitation data from a principal station with its neighbouring station located in Alor Setar, Kedah, Malaysia. GEP is\nan extension to genetic programming (GP), and can provide simple and efficient solution. The study illustrates the applications of\nGEP to determine the most suitable rainfall station to replace the principal rainfall station (station 6103047). This is to ensure that\na reliable rainfall station can be made if the principal station malfunctioned. These were done by comparing principal station data\nwith each individual neighbouring station. Result of the analysis reveals that the station 38 is the most compatible to the principal\nstation where the value of R2 is 0.886.
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