Application of Random Forest Algorithm in Xijiang River Flood Forecasting
Based on the measured flood data from 1952 to 2005 in Qianjiang Station,Liuzhou Station,and Wuxuan Station of Xijiang River,this paper selects the characteristic factors of flood forecasting by analyzing the correlation of flood flow at upstream and downstream stations.Meanwhile,the random forest al...
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Editorial Office of Pearl River
2023-01-01
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| Series: | Renmin Zhujiang |
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| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2023.10.014 |
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| author | LIU Hechang ZHAO Bohua SUN Bo |
| author_facet | LIU Hechang ZHAO Bohua SUN Bo |
| author_sort | LIU Hechang |
| collection | DOAJ |
| description | Based on the measured flood data from 1952 to 2005 in Qianjiang Station,Liuzhou Station,and Wuxuan Station of Xijiang River,this paper selects the characteristic factors of flood forecasting by analyzing the correlation of flood flow at upstream and downstream stations.Meanwhile,the random forest algorithm is adopted to build a flood forecasting model for Wuxuan Station.The results are as follows.The certainty coefficients of the 12~48 h flood process in the studied station during the calibration period are more than 0.98 with the pass rates more than 98%.Additionally,the certainty coefficients of the 12~24 h flood process during the verification period are more than 0.72,with a pass rate of more than 82%.Thus,the proposed model has high forecast accuracy and little uncertainty and can provide a reference for flood forecasting methods. |
| format | Article |
| id | doaj-art-0b0aac137a30475490bd44a8de594287 |
| institution | Kabale University |
| issn | 1001-9235 |
| language | zho |
| publishDate | 2023-01-01 |
| publisher | Editorial Office of Pearl River |
| record_format | Article |
| series | Renmin Zhujiang |
| spelling | doaj-art-0b0aac137a30475490bd44a8de5942872025-01-15T02:21:47ZzhoEditorial Office of Pearl RiverRenmin Zhujiang1001-92352023-01-014447637114Application of Random Forest Algorithm in Xijiang River Flood ForecastingLIU HechangZHAO BohuaSUN BoBased on the measured flood data from 1952 to 2005 in Qianjiang Station,Liuzhou Station,and Wuxuan Station of Xijiang River,this paper selects the characteristic factors of flood forecasting by analyzing the correlation of flood flow at upstream and downstream stations.Meanwhile,the random forest algorithm is adopted to build a flood forecasting model for Wuxuan Station.The results are as follows.The certainty coefficients of the 12~48 h flood process in the studied station during the calibration period are more than 0.98 with the pass rates more than 98%.Additionally,the certainty coefficients of the 12~24 h flood process during the verification period are more than 0.72,with a pass rate of more than 82%.Thus,the proposed model has high forecast accuracy and little uncertainty and can provide a reference for flood forecasting methods.http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2023.10.014flood forecastingrandom forest algorithmcorrelation analysisdata miningforecast characteristic factors |
| spellingShingle | LIU Hechang ZHAO Bohua SUN Bo Application of Random Forest Algorithm in Xijiang River Flood Forecasting Renmin Zhujiang flood forecasting random forest algorithm correlation analysis data mining forecast characteristic factors |
| title | Application of Random Forest Algorithm in Xijiang River Flood Forecasting |
| title_full | Application of Random Forest Algorithm in Xijiang River Flood Forecasting |
| title_fullStr | Application of Random Forest Algorithm in Xijiang River Flood Forecasting |
| title_full_unstemmed | Application of Random Forest Algorithm in Xijiang River Flood Forecasting |
| title_short | Application of Random Forest Algorithm in Xijiang River Flood Forecasting |
| title_sort | application of random forest algorithm in xijiang river flood forecasting |
| topic | flood forecasting random forest algorithm correlation analysis data mining forecast characteristic factors |
| url | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2023.10.014 |
| work_keys_str_mv | AT liuhechang applicationofrandomforestalgorithminxijiangriverfloodforecasting AT zhaobohua applicationofrandomforestalgorithminxijiangriverfloodforecasting AT sunbo applicationofrandomforestalgorithminxijiangriverfloodforecasting |