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GM(1,1)改進(jìn)模型的在智慧水務(wù)中的研究與應用
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博創(chuàng )(1401801)、西南交大合作智慧水務(wù)項目(1200305)、唐山市室內定位重點(diǎn)實(shí)驗室建設項目(220020502)


Research and Application of GM(1,1) Improved Model in Smart WaterZhang Yihang1 , Qian Xiaoqun2, Peng Hongyu3
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    摘要:

    智慧水務(wù)是智慧城市的重要組成部分,水資源合理的分配調度更是智慧水務(wù)系統中的重中之重,如何準確快速的預測未來(lái)某時(shí)的指標數據在調度過(guò)程中尤為關(guān)鍵。通過(guò)對智慧水務(wù)的供水模型進(jìn)行了研究,提出了預測模型的應用方案,驗證了其在工程中的合理性。在預測模型的研究中,首先采用了經(jīng)典的均值GM(1,1)模型對水流量序列進(jìn)行預測,并在此基礎上引入馬爾科夫鏈,使用單步和多步加權分別對GM(1,1)模型的誤差進(jìn)行分析和預測,對其結果進(jìn)行了矯正,最后使用MATLAB對三種方式進(jìn)行了計算和仿真。比較結果顯示馬爾科夫鏈與GM(1,1)模型的結合比單純的GM(1,1)模型在預測精度上有較大提升,而加權之后馬爾科夫的矯正效果比單步的矯正效果更好。

    Abstract:

    Smart water is an important part of smart cities. The rational allocation of water resources is one of the most significant step in smart water systems. How to predict the future index data accurately and quickly is particularly critical in the scheduling process. Through the study of the smart water supply model, the application scheme of the forecasting model is put forward, and the rationality of the forecasting model in the project is verified. In the study of forecasting model, the classical mean GM (1,1) model is used to predict the water flow series firstly. On this basis, Markov chain is introduced to analyze and predict the errors of GM (1,1) model by using single-step and multi-step weighting, and the results are corrected. Finally, MATLAB was used to calculate and simulate the three methods. The comparison results show that the combination of Markov chain and GM (1,1) model has a greater improvement in prediction accuracy than the simple GM (1,1) model. The Markov chain after weighting is also improved in accuracy compared to the single-step prediction state.

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張一航,錢(qián)曉群,彭宏玉. GM(1,1)改進(jìn)模型的在智慧水務(wù)中的研究與應用計算機測量與控制[J].,2019,27(7):119-123.

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歷史
  • 收稿日期:2018-11-26
  • 最后修改日期:2019-06-28
  • 錄用日期:2018-12-27
  • 在線(xiàn)發(fā)布日期: 2019-07-29
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