【摘要】：標(biāo)度指數(shù)計算的即時性與準確性對相關(guān)時間序列的動力學(xué)結(jié)構(gòu)突變分析至關(guān)重要,然而現(xiàn)有方法在即時性與準確性上一直無法兼顧.將小波分析方法與滑動移除窗口技術(shù)相融合,提出一種新的動力學(xué)結(jié)構(gòu)突變檢測方法——滑動移除小波分析法.通過選取不同的滑動移除窗口,分別對構(gòu)建的線性、非線性理想時間序列進行動力學(xué)結(jié)構(gòu)突變分析,結(jié)果表明不論是線性時間序列還是非線性時間序列,滑動移除小波分析能夠準確地檢測到序列的動力學(xué)結(jié)構(gòu)突變點及突變區(qū)間,對于滑動移除窗口長度依賴性較小,具有很強的穩(wěn)定性,而且在計算速度上明顯優(yōu)于滑動移除重標(biāo)極差和滑動移除方差分析方法,將在大數(shù)據(jù)處理中具有一定的優(yōu)勢.同時分別對線性、非線性理想時間序列添加高斯白噪聲,結(jié)果表明滑動移除小波分析具有很強的抗噪能力,能夠準確地檢測到加噪后序列的突變點.對佛坪站日最高溫度實測資料的動力學(xué)結(jié)構(gòu)突變的準確檢測進一步驗證了該方法的有效性.滑動移除小波分析法可為具有相關(guān)性的系統(tǒng)動力學(xué)結(jié)構(gòu)突變的快速、準確檢測提供一種途徑.
[Abstract]:The timeliness and accuracy of scale index calculation are very important to the sudden change analysis of dynamic structure of related time series. However, the existing methods have been unable to take into account both timeliness and accuracy. A new dynamic structure mutation detection method, sliding removal wavelet analysis, is proposed by combining wavelet analysis method with sliding removal window technique. By selecting different sliding removal windows, the dynamic structure mutation analysis of the constructed linear and nonlinear ideal time series is carried out respectively. the results show that the sliding removal wavelet analysis can accurately detect the dynamic structure mutation point and mutation interval of the sequence, and has strong stability for the length dependence of the sliding removal window. Moreover, the calculation speed is obviously better than that of sliding removal rescaling pole difference and sliding removal variance analysis method, which will have some advantages in big data treatment. At the same time, Gaussian white noise is added to linear and nonlinear ideal time series respectively. the results show that sliding removal wavelet analysis has strong anti-noise ability and can accurately detect the mutation point of noisy sequence. The effectiveness of the method is further verified by the accurate detection of the dynamic structure mutation of the measured data of the daily maximum temperature in Foping station. Sliding removal wavelet analysis can provide a way to detect the sudden change of dynamic structure of the system quickly and accurately.
【作者單位】： 長安大學(xué)環(huán)境科學(xué)與工程學(xué)院旱區(qū)地下水文與生態(tài)效應(yīng)教育部重點實驗室;西安理工大學(xué)水利水電學(xué)院西北旱區(qū)生態(tài)水利工程國家重點實驗室培育基地;
【基金】：國家自然科學(xué)基金青年科學(xué)基金(批準號:51409005);國家自然科學(xué)基金重大項目(批準號:51190093);國家自然科學(xué)基金(批準號:51379014) 中央高�；究蒲袠I(yè)務(wù)費專項資金(批準號:310829161008)資助的課題~~
【分類號】：N941.3;O211.61

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