Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model
In the settlement monitoring,the amount of initial monitoring data is little with great changes.It can effectively enhance the correlation of the data series and improve the accuracy of the model through pre-processing the data and modeling with GM prediction model.In view of the single value of wei...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Pearl River
2020-01-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2020.11.011 |
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| _version_ | 1841535637761556480 |
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| author | LI Xuede ZHOU Mingming ZHAO Jinlei LIU Yang JIANG Wenzhi WANG Guizhi |
| author_facet | LI Xuede ZHOU Mingming ZHAO Jinlei LIU Yang JIANG Wenzhi WANG Guizhi |
| author_sort | LI Xuede |
| collection | DOAJ |
| description | In the settlement monitoring,the amount of initial monitoring data is little with great changes.It can effectively enhance the correlation of the data series and improve the accuracy of the model through pre-processing the data and modeling with GM prediction model.In view of the single value of weight coefficient in the traditional GM prediction model,this paper selects the optimal weight coefficient for the establishment of the GM prediction model by introducing superimposed weight coefficients and changing the initial value.The results show that the improved GM prediction model with high accuracy can accurately predict the actual measured value. |
| format | Article |
| id | doaj-art-9191ac11916a41d8b0a2f32ec1c00469 |
| institution | Kabale University |
| issn | 1001-9235 |
| language | zho |
| publishDate | 2020-01-01 |
| publisher | Editorial Office of Pearl River |
| record_format | Article |
| series | Renmin Zhujiang |
| spelling | doaj-art-9191ac11916a41d8b0a2f32ec1c004692025-01-15T02:30:49ZzhoEditorial Office of Pearl RiverRenmin Zhujiang1001-92352020-01-014147650885Study on Prediction of Sluice Settlement Based on Improved GM (1,1) ModelLI XuedeZHOU MingmingZHAO JinleiLIU YangJIANG WenzhiWANG GuizhiIn the settlement monitoring,the amount of initial monitoring data is little with great changes.It can effectively enhance the correlation of the data series and improve the accuracy of the model through pre-processing the data and modeling with GM prediction model.In view of the single value of weight coefficient in the traditional GM prediction model,this paper selects the optimal weight coefficient for the establishment of the GM prediction model by introducing superimposed weight coefficients and changing the initial value.The results show that the improved GM prediction model with high accuracy can accurately predict the actual measured value.http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2020.11.011superimposed weight coefficientGM modelsmall sample datasluice settlement safety monitoring |
| spellingShingle | LI Xuede ZHOU Mingming ZHAO Jinlei LIU Yang JIANG Wenzhi WANG Guizhi Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model Renmin Zhujiang superimposed weight coefficient GM model small sample data sluice settlement safety monitoring |
| title | Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model |
| title_full | Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model |
| title_fullStr | Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model |
| title_full_unstemmed | Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model |
| title_short | Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model |
| title_sort | study on prediction of sluice settlement based on improved gm 1 1 model |
| topic | superimposed weight coefficient GM model small sample data sluice settlement safety monitoring |
| url | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2020.11.011 |
| work_keys_str_mv | AT lixuede studyonpredictionofsluicesettlementbasedonimprovedgm11model AT zhoumingming studyonpredictionofsluicesettlementbasedonimprovedgm11model AT zhaojinlei studyonpredictionofsluicesettlementbasedonimprovedgm11model AT liuyang studyonpredictionofsluicesettlementbasedonimprovedgm11model AT jiangwenzhi studyonpredictionofsluicesettlementbasedonimprovedgm11model AT wangguizhi studyonpredictionofsluicesettlementbasedonimprovedgm11model |