SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis
In view of the multi-scale non-stationarity and other characteristics of monthly runoff in hydrological time series,this paper proposes a singular spectrum decomposition (SSD)-based model of combined monthly runoff forecasting that integrates the student psychology based optimization (SPBO) algorith...
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Editorial Office of Pearl River
2022-01-01
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| Series: | Renmin Zhujiang |
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| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2022.05.020 |
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| author | ZHANG Yajie CUI Dongwen |
| author_facet | ZHANG Yajie CUI Dongwen |
| author_sort | ZHANG Yajie |
| collection | DOAJ |
| description | In view of the multi-scale non-stationarity and other characteristics of monthly runoff in hydrological time series,this paper proposes a singular spectrum decomposition (SSD)-based model of combined monthly runoff forecasting that integrates the student psychology based optimization (SPBO) algorithm with the adaptive network based fuzzy inference system (ANFIS),namely the SSD-SPBO-ANFIS model.This model is then applied to the monthly runoff forecasting at a hydrological station in Yunnan Province.Specifically,time series data of sample monthly runoff are decomposed into various independent sub-series components through SSD to reduce the complexity of the time series data;then,the principle of the SPBO algorithm is outlined,and eight standard functions are selected for simulation verification and comparison of the SPBO algorithm;finally,the SPBO algorithm is employed to optimize the ANFIS condition and conclusion parameters.The SSD-SPBO-ANFIS model is built to forecast each sub-series,which is then superimposed to obtain the final monthly runoff forecasting result.In addition,the results of the proposed model are compared with those of the ensemble empirical mode decomposition (EEMD)-based EEMD-SPBO-ANFIS model and the SPBO-ANFIS model without decomposition.The following observations can be made from the results:The SPBO algorithm has favorable optimization accuracy;with a mean absolute percentage error of 5.57%,a mean absolute error of 0.20 m<sup>3</sup>/s,a Nash coefficient of 0.994 8,and a pass rate of 96.7%,the SSD-SPBO-ANFIS model has an effect better than that of the EEMD-SPBO-ANFIS model and far better than that of the SPBO-ANFIS model in forecasting sample monthly runoff.The proposed model and method can provide references for related research on hydrological time series forecasting. |
| format | Article |
| id | doaj-art-3921455221d64b1e9b4edcf9b9104981 |
| institution | Kabale University |
| issn | 1001-9235 |
| language | zho |
| publishDate | 2022-01-01 |
| publisher | Editorial Office of Pearl River |
| record_format | Article |
| series | Renmin Zhujiang |
| spelling | doaj-art-3921455221d64b1e9b4edcf9b91049812025-01-15T02:27:15ZzhoEditorial Office of Pearl RiverRenmin Zhujiang1001-92352022-01-014347644960SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum AnalysisZHANG YajieCUI DongwenIn view of the multi-scale non-stationarity and other characteristics of monthly runoff in hydrological time series,this paper proposes a singular spectrum decomposition (SSD)-based model of combined monthly runoff forecasting that integrates the student psychology based optimization (SPBO) algorithm with the adaptive network based fuzzy inference system (ANFIS),namely the SSD-SPBO-ANFIS model.This model is then applied to the monthly runoff forecasting at a hydrological station in Yunnan Province.Specifically,time series data of sample monthly runoff are decomposed into various independent sub-series components through SSD to reduce the complexity of the time series data;then,the principle of the SPBO algorithm is outlined,and eight standard functions are selected for simulation verification and comparison of the SPBO algorithm;finally,the SPBO algorithm is employed to optimize the ANFIS condition and conclusion parameters.The SSD-SPBO-ANFIS model is built to forecast each sub-series,which is then superimposed to obtain the final monthly runoff forecasting result.In addition,the results of the proposed model are compared with those of the ensemble empirical mode decomposition (EEMD)-based EEMD-SPBO-ANFIS model and the SPBO-ANFIS model without decomposition.The following observations can be made from the results:The SPBO algorithm has favorable optimization accuracy;with a mean absolute percentage error of 5.57%,a mean absolute error of 0.20 m<sup>3</sup>/s,a Nash coefficient of 0.994 8,and a pass rate of 96.7%,the SSD-SPBO-ANFIS model has an effect better than that of the EEMD-SPBO-ANFIS model and far better than that of the SPBO-ANFIS model in forecasting sample monthly runoff.The proposed model and method can provide references for related research on hydrological time series forecasting.http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2022.05.020runoff forecastingsingular spectrum analysisstudent psychology based optimization algorithmadaptive network based fuzzy inference systemsimulation test |
| spellingShingle | ZHANG Yajie CUI Dongwen SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis Renmin Zhujiang runoff forecasting singular spectrum analysis student psychology based optimization algorithm adaptive network based fuzzy inference system simulation test |
| title | SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis |
| title_full | SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis |
| title_fullStr | SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis |
| title_full_unstemmed | SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis |
| title_short | SPBO-ANFIS Model of Combined Monthly Runoff Forecasting Based on Singular Spectrum Analysis |
| title_sort | spbo anfis model of combined monthly runoff forecasting based on singular spectrum analysis |
| topic | runoff forecasting singular spectrum analysis student psychology based optimization algorithm adaptive network based fuzzy inference system simulation test |
| url | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2022.05.020 |
| work_keys_str_mv | AT zhangyajie spboanfismodelofcombinedmonthlyrunoffforecastingbasedonsingularspectrumanalysis AT cuidongwen spboanfismodelofcombinedmonthlyrunoffforecastingbasedonsingularspectrumanalysis |