人民黄河
人民黃河
인민황하
Yellow River
2015年
10期
42-45
,共4页
db5小波%sym8小波%Anfis模型%年最大洪峰流量预测%张家庄水库
db5小波%sym8小波%Anfis模型%年最大洪峰流量預測%張傢莊水庫
db5소파%sym8소파%Anfis모형%년최대홍봉류량예측%장가장수고
wavelet-db5%wavelet-sym8%ANFIS model%annual maximum peak discharge forecast%Zhangjiazhuang Reservoir
洪水的非线性变化特征使其预测结果在防汛指挥中难以让决策者实时有效利用,基于此,提出两种小波-ANFIS模型,将其应用于张家庄水库的年最大洪峰流量预测中,从而选出预测效果较好者。首先拟合1973—2002年的原始数据S,利用不同小波分解函数db5和sym8,分别对S信号进行尺度为4的分解,得到两组系列的低、高频信号;然后利用各低、高频信号对ANFIS模型进行训练,调试得到最佳模型并用来预测各低、高频信号在2003—2007年的信息;最后将各系列低、高频预测信号进行重构,即生成由sym8-ANFIS和db5-ANFIS模型预测的两个序列。经比较分析,sym8-ANFIS模型具有较快的收敛速度,且精度更高。
洪水的非線性變化特徵使其預測結果在防汛指揮中難以讓決策者實時有效利用,基于此,提齣兩種小波-ANFIS模型,將其應用于張傢莊水庫的年最大洪峰流量預測中,從而選齣預測效果較好者。首先擬閤1973—2002年的原始數據S,利用不同小波分解函數db5和sym8,分彆對S信號進行呎度為4的分解,得到兩組繫列的低、高頻信號;然後利用各低、高頻信號對ANFIS模型進行訓練,調試得到最佳模型併用來預測各低、高頻信號在2003—2007年的信息;最後將各繫列低、高頻預測信號進行重構,即生成由sym8-ANFIS和db5-ANFIS模型預測的兩箇序列。經比較分析,sym8-ANFIS模型具有較快的收斂速度,且精度更高。
홍수적비선성변화특정사기예측결과재방신지휘중난이양결책자실시유효이용,기우차,제출량충소파-ANFIS모형,장기응용우장가장수고적년최대홍봉류량예측중,종이선출예측효과교호자。수선의합1973—2002년적원시수거S,이용불동소파분해함수db5화sym8,분별대S신호진행척도위4적분해,득도량조계렬적저、고빈신호;연후이용각저、고빈신호대ANFIS모형진행훈련,조시득도최가모형병용래예측각저、고빈신호재2003—2007년적신식;최후장각계렬저、고빈예측신호진행중구,즉생성유sym8-ANFIS화db5-ANFIS모형예측적량개서렬。경비교분석,sym8-ANFIS모형구유교쾌적수렴속도,차정도경고。
Aiming at the difficulty for decision-makers to make effective and real-time decision-making in flood control,this paper put forward two models based on the Wavelet-Anfis method and these were applied in prediction of Zhangjiazhuang Reservoir about its annual maximum peak discharge. Firstly,the original data S from 1973 to 2002 was fit,then respectively decomposed with the db5 and sym8 at scale 4 for the low-frequency and high-frequency signals. Secondly,the signals were trained and debugged for the respective best model to forecast the low-frequency and high-frequency signals from 2003 to 2007. Finally,two prediction sequences were generated by the predicted signals rebuilt by sym8-Anfis and db5-Anfis model. By comparison analysis,sym8-Anfis model has a faster convergence rate and higher accuracy,and it has important reference value for the annual maximum flood peak flow prediction and the corresponding decision.