A Recursive Approach to Long-Term Prediction of Monthly Precipitation Using Genetic Programming
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- @Article{liu:2019:WRM,
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author = "Suning Liu and Haiyun Shi",
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title = "A Recursive Approach to {Long-Term} Prediction of
Monthly Precipitation Using Genetic Programming",
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journal = "Water Resources Management",
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year = "2019",
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volume = "33",
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number = "3",
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pages = "1103--1121",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://link.springer.com/article/10.1007/s11269-018-2169-0",
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DOI = "doi:10.1007/s11269-018-2169-0",
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abstract = "Precipitation is regarded as the basic component of
the global hydrological cycle. This study develops a
recursive approach to long-term prediction of monthly
precipitation using genetic programming (GP), taking
the Three-River Headwaters Region (TRHR) in China as
the study area. The daily precipitation data recorded
at 29 meteorological stations during 1961 thru 2014 are
collected, among which the data during 1961 to 2000 are
for calibration and the remaining data are for
validation. To develop this approach, first, the
preliminary estimations of annual precipitation are
computed based on a statistical method. Second, the
percentage of the monthly precipitation for each month
of a year is calculated as the mean monthly
precipitation divided by the mean annual precipitation
during the study period, and then the preliminary
estimation of monthly precipitation for each month of a
year is obtained. Third, since GP can be used to
improve the prediction results through establishing the
relationship of the observations with the preliminary
estimations at the past and current times, it is
adopted to improve the preliminary estimations. The
calibration and validation results reveal that the
recursive approach involving GP can provide the more
accurate predictions of monthly precipitation. Finally,
this approach is used to predict the monthly
precipitation over the TRHR till 2050. Overall, the
proposed method and the obtained results will enhance
our understanding and facilitate future studies
regarding the long-term prediction of precipitation in
such regions.",
- }
Genetic Programming entries for
Suning Liu
Haiyun Shi
Citations