發(fā)布時(shí)間：2018-02-21 05:17

  本文關(guān)鍵詞： 極移預(yù)報(bào) 最小二乘支持向量機(jī) GM(1 1) 經(jīng)驗(yàn)?zāi)Ｊ椒纸?大氣角動(dòng)量 海洋角動(dòng)量　出處：《中南大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：摘要：高精度的地球定向參數(shù)(EOP)具有重要的科學(xué)意義和實(shí)際應(yīng)用價(jià)值。EOP是天球參考框架和地球參考框架之間轉(zhuǎn)換的必要條件；同時(shí),深空探測和衛(wèi)星導(dǎo)航等領(lǐng)域?qū)OP的預(yù)報(bào)值呈現(xiàn)出日益增長的需求。 現(xiàn)代測地技術(shù)(VLBI, GPS, SLR等)是獲取EOP的主要手段,但是由于復(fù)雜的數(shù)據(jù)處理過程,獲取EOP往往存在時(shí)間延遲。為了滿足EOP使用的實(shí)時(shí)性需求,國內(nèi)外廣泛開展了EOP預(yù)報(bào)的相關(guān)研究。目前,EOP中的UT1-UTC、日長變化和歲差章動(dòng)模型都取得了較為實(shí)用的預(yù)報(bào)成果。但是在極移預(yù)報(bào)方面,由于其自身激發(fā)機(jī)理的復(fù)雜性,預(yù)報(bào)結(jié)果并不很理想。因此,作為EOP預(yù)報(bào)的重要組成部分,極移預(yù)報(bào)是一項(xiàng)值得深入研究的工作。 本文主要進(jìn)行改進(jìn)極移預(yù)報(bào)的相關(guān)研究,主要從兩方面著手,一是改進(jìn)模型的預(yù)報(bào),主要改善神經(jīng)網(wǎng)絡(luò)中最新的一種模型——最小二乘支持向量機(jī)；二是完善物理建模的預(yù)報(bào),引入大氣、海洋激發(fā)源。 主要研究內(nèi)容如下： (1)將最小二乘支持向量機(jī)應(yīng)用于極移序列的預(yù)報(bào)中。地球定向參數(shù)包含復(fù)雜的非線性因素,應(yīng)用非線性模型進(jìn)行預(yù)報(bào)是較好的選擇途徑之一。本文將新的機(jī)器學(xué)習(xí)模型——最小二乘支持向量機(jī)應(yīng)用于極移預(yù)報(bào),該模型能夠更好的處理包含非線性因素的數(shù)據(jù)。實(shí)驗(yàn)結(jié)果證明了將該模型應(yīng)用于極移預(yù)報(bào)中具有可行性和有效性。 (2)由于單一模型對于極移殘差序列預(yù)報(bào)的改善有限。GM(1,1)因具有簡單有效,易于編程實(shí)現(xiàn)等優(yōu)點(diǎn)被廣泛應(yīng)用于預(yù)測領(lǐng)域。但是該模型適合短期預(yù)報(bào)。本文嘗試將最小二乘支持向量機(jī)和GM(1,1)模型的組合模型應(yīng)用于極移殘差序列的預(yù)報(bào)中。實(shí)驗(yàn)結(jié)果證明了該組合模型對1-10天的超短期預(yù)報(bào)精度有改善。 (3)將經(jīng)驗(yàn)?zāi)Ｊ椒纸鈶?yīng)用到極移短期預(yù)報(bào)中�？紤]到極移包含的高頻信號對于極移短期預(yù)報(bào)有阻礙作用。經(jīng)驗(yàn)?zāi)Ｊ椒纸饽軌虺浞直Ａ粜盘柋旧頁碛械姆瞧椒�(wěn)和非線性特征；具有自適應(yīng)能力強(qiáng)；對信號類型沒有限制等特點(diǎn)。本文采用經(jīng)驗(yàn)?zāi)Ｊ椒纸鈱O移序列進(jìn)行分解,去除高頻信號,然后基于最小二乘外推模型和最小二乘支持向量機(jī)模型的組合模型對去除高頻信號的重構(gòu)極移序列進(jìn)行1-30天的短期預(yù)報(bào)。實(shí)驗(yàn)結(jié)果表明,將該模型應(yīng)用到極移短期預(yù)報(bào)具有可行性,預(yù)報(bào)精度有明顯改善。 (4)考慮大氣、海洋和極移具有相關(guān)性,將大氣和海洋角動(dòng)量χ1、χ2序列通過積分轉(zhuǎn)換到極移域中,獲得由大氣、海洋激發(fā)的極移序列；在預(yù)報(bào)模型中分別加入這兩個(gè)激發(fā)序列。實(shí)驗(yàn)結(jié)果表明,加入激發(fā)的極移序列以后,預(yù)報(bào)精度有改善。 同時(shí),考慮大氣和海洋角動(dòng)量既有方向又有大小,首次將大氣和海洋角動(dòng)量看作矢量,進(jìn)行矢量和計(jì)算。實(shí)驗(yàn)結(jié)果表明,在預(yù)報(bào)模型中加入由大氣和海洋聯(lián)合激發(fā)的極移序列以后,極移的預(yù)報(bào)精度有改善。 但是,對于激發(fā)源和加入方式的選擇,并沒有獲得明確的結(jié)論,這一定程度也說明了極移激發(fā)的復(fù)雜性。
[Abstract]:Abstract: the earth orientation parameters with high precision (EOP) has important scientific significance and practical application value of.EOP is a necessary condition for transformation between the celestial reference frame and earth reference frame; at the same time, the forecast of EOP in deep space exploration and satellite navigation value showing a growing demand.
Modern geodetic techniques (VLBI, GPS, SLR) is the main means of access to EOP, but due to the complexity of data processing, to obtain EOP time delay often exists. In order to meet the needs of real-time EOP used widely at home and abroad, to carry out related research EOP prediction. At present, EOP in UT1-UTC, changes in length of day and nutation models have more practical forecasting results. But the pole shift in forecasting, because of its complexity and excitation mechanism, the forecasting result is not very satisfactory. Therefore, as an important part of EOP forecast, forecast the pole shift is a worthy of further study.
This paper mainly research the pole shift improved forecast, mainly from two aspects, one is to improve the model prediction, mainly to improve a new model of neural network and least squares support vector machines; the two is to improve the physical modeling forecast, into the atmosphere, ocean excitation source.
The main contents are as follows:
(1) the least squares support vector machine is used to shift sequence prediction. Earth orientation parameters contain complex nonlinear factors, the application of nonlinear model prediction is one of the best approaches. This paper will choose the new machine learning model, least squares support vector machine for polar motion prediction, the model can better handle contain data nonlinear factors. The experimental result shows that the model is applied to the pole shift is feasible and effective in forecasting.
(2) due to the single model for the pole shift residuals prediction (1,1) for improving.GM Co. which is simple and effective, easy programming is widely used in the field of forecasting. But the model is suitable for short-term forecasting. This paper attempts to apply the least squares support vector machine (1,1) model and GM combined model is applied to the pole shift error sequence prediction. Experimental results show that the combined model has improved on the 1-10 day of the ultra short term forecast accuracy.
(3) the application of empirical mode decomposition to the shift in the short-term forecasting. Considering the high frequency shift signal contains the pole shift for short-term forecasting hinders. EMD can fully retain the signal itself has the nonlinear and non-stationary characteristics; has strong adaptive ability; no restrictions on the signal characteristics of the type. Empirical mode decomposition of the pole shift sequence, removing the high frequency signal, then the combination model of least square extrapolation model and least squares support vector machine model to remove the high frequency signal reconstruction shift sequence forecast based on 1-30 day. The experimental results show that the model is applied to the feasibility of the pole shift forecast, forecast accuracy is obviously to improve.
(4) considering the atmosphere, oceans and the pole shift will have correlation, atmospheric and oceanic angular momentum x 1, x 2 sequence conversion to the shift in the integral domain, obtained by the atmosphere, the pole shift sequence of oceanic excitations; these two sequences were added to stimulate in the forecasting model. The experimental results show that adding excitation after the pole shift sequence, the prediction accuracy has improved.
At the same time, considering the atmospheric and oceanic angular momentum is the direction and size of the atmospheric and oceanic angular momentum as a vector, vector and calculation. Experimental results show that adding in the forecast models inspired by the atmosphere and ocean with the pole shift sequence after the pole shift, forecast precision has improved.
However, there is no definite conclusion for the choice of excitation source and the way of joining, which also explains the complexity of the pole shift excitation to some extent.

【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P127.4

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