本文關(guān)鍵詞：非線性分形理論與時(shí)間序列分析法在土壤含水量預(yù)測(cè)中的應(yīng)用研究　出處：《長(zhǎng)安大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 時(shí)間序列 分形維數(shù) R/S分析法 去趨勢(shì)波動(dòng)分析法 自回歸模型

【摘要】：土壤中水分的含量直接影響著農(nóng)作物的生長(zhǎng),要準(zhǔn)確預(yù)測(cè)水分所占的比例并進(jìn)行適時(shí)的灌溉,需要我們充分地掌握其動(dòng)態(tài)變化規(guī)律;但在實(shí)際中,土壤含水量變化受很多因素的影響,其變化規(guī)律極其復(fù)雜,呈現(xiàn)出非線性特征。因此,針對(duì)這種復(fù)雜的非線性特征,本文以分形理論為基礎(chǔ),采用時(shí)間序列分析法,對(duì)新疆阜康農(nóng)田土壤含水量實(shí)測(cè)數(shù)據(jù)進(jìn)行了研究,并對(duì)土壤含水量未來的變化趨勢(shì)進(jìn)行了預(yù)測(cè),得到了一些有價(jià)值的結(jié)論。具體的研究步驟如下:(1)采用R/S分析法,對(duì)新疆阜康農(nóng)田土壤含水量實(shí)測(cè)數(shù)據(jù)時(shí)間序列的Hurst指數(shù)和分形維數(shù)進(jìn)行了分析對(duì)比,得到了土壤含水量具有長(zhǎng)期的持續(xù)性特征。研究結(jié)果顯示:10cm,80cm,150cm三個(gè)不同層的Hurst指數(shù)都大于0.5小于1,表明新疆阜康農(nóng)田土壤含水量時(shí)間序列為非隨機(jī)時(shí)間序列,時(shí)間序列存在著明顯的長(zhǎng)程相關(guān)性,該時(shí)間序列是持續(xù)性的。該地區(qū)時(shí)間序列的分形維數(shù)大于1小于2,表明該地區(qū)的土壤含水量變化的波動(dòng)幅度隨著深度的增加而逐漸變小。(2)采用去趨勢(shì)波動(dòng)分析法,對(duì)新疆阜康農(nóng)田14個(gè)不同深度的土壤含水量時(shí)間序列的長(zhǎng)程相關(guān)性進(jìn)行了定量分析,并結(jié)合分形維數(shù),研究了該地區(qū)土壤含水量的動(dòng)態(tài)變化規(guī)律。研究結(jié)果顯示:這14個(gè)不同深度的土壤含水量時(shí)間序列的標(biāo)度指數(shù)隨著土壤深度的增加而逐漸增大,即:該地區(qū)土壤含水量時(shí)間序列的長(zhǎng)程相關(guān)性隨著深度的增加而逐漸加強(qiáng)。分形維數(shù)的增加,揭示了土壤含水量變化的波動(dòng)幅度隨著深度的增加而逐漸趨于穩(wěn)定。(3)本文采用了三種自回歸模型,對(duì)新疆阜康農(nóng)田土壤含水量進(jìn)行了預(yù)測(cè),得到了3種土壤含水量時(shí)間序列最理想的時(shí)間延滯。研究結(jié)果顯示:季節(jié)的變化對(duì)土壤含水量的影響十分明顯,這就要求我們?cè)跍?zhǔn)確預(yù)測(cè)土壤水分含量的同時(shí),要更加關(guān)注季節(jié)的變化對(duì)降雨量的影響,以便得到更為準(zhǔn)確的結(jié)論。
[Abstract]:Soil moisture content directly affects the growth of crops. To accurately predict the proportion of water and carry out timely irrigation, we need to fully grasp its dynamic change law; However, in practice, the variation of soil water content is influenced by many factors, and its variation law is extremely complex, showing nonlinear characteristics. Therefore, this paper is based on fractal theory in view of this complex nonlinear characteristics. Time series analysis was used to study the measured data of farmland soil moisture in Fukang, Xinjiang, and the trend of soil water content in the future was predicted. Some valuable conclusions are obtained. The specific research steps are as follows: 1) the R / S method is used. The Hurst exponent and fractal dimension of the time series of measured soil water content data in Fukang Xinjiang were analyzed and compared. The results showed that the Hurst index of the three different layers was more than 0. 5 < 1. 5. The results showed that the time series of farmland soil moisture content in Fukang Xinjiang was a non-random time series, and the time series had obvious long-term correlation. The fractal dimension of the time series in this region is greater than 1 and less than 2. The results showed that the fluctuation range of soil water content in this area gradually decreased with the increase of depth. 2) De-trend fluctuation analysis method was used. The long-term correlation of 14 soil moisture content time series of different depths in Fukang farmland in Xinjiang was quantitatively analyzed and combined with fractal dimension. The dynamic variation of soil water content in this area was studied. The results showed that the scale index of the time series of 14 different depths of soil moisture increased with the increase of soil depth. That is, the long-term correlation of the time series of soil water content in this area is gradually strengthened with the increase of depth, and the fractal dimension increases. It was revealed that the fluctuation range of soil moisture content tended to be stable with the increase of soil depth.) in this paper, three kinds of autoregressive models were used to predict the soil water content of Fukang farmland in Xinjiang. The results show that the seasonal variation has a very obvious effect on soil moisture content, which requires us to accurately predict the soil moisture content at the same time. More attention should be paid to the effects of seasonal changes on rainfall in order to obtain more accurate conclusions.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：S152.7;O212.1

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