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1.
??????????????????????????±???????????÷????????????????????t??????????????????з?????в????????????????????????????к???????з???????????????????????????????????????????÷???????????GM(1??1)??AR??LSSVM??????  相似文献   

2.
??о?GM(1,1)???????????????????????????????????????GM(1,1)????????????????Σ?????3′?л???????????????????????????????????RnGM???????????????RnGM????????е????????????GM(1,1)????????????б????????????RnGM???н????????????????????  相似文献   

3.
?о???????????????????????????????????????GM-arkov????????????????????PSO?????GM??1??1???????????????????????????????????е???????????н??????????????????????????????????????????????GM-arkov?????GM(1,1????????????б????????????????GM-arkov????????????????????GM??1??1????  相似文献   

4.
???????????????????????????????????????ARIMA???????????????????????1?????????????????????????????з???????????????????????β???????????????????????MA????????????????????????ARIMA??0??2??q?????????????????????????ARIMA??0??2??q?????????????????????ζ?????????????  相似文献   

5.
???????????鳡1998??2004??????????????????????о??????????????仯?????????????????????????????仯????????????2001??10?????6.0??2001??1?????6.5??2003??7?′??6.2??2003??10?′??6.1????????н???????  相似文献   

6.
GPS Block IIR(M)����ԭ�����Ӳ�Ԥ���о�   总被引:3,自引:0,他引:3  
?????????????????£????ú?????????GPS Block IIR??M??????????????????????о??????????GM(1??1)??AR(p)??????????1???????????????1 ns????????10??????????????10 ns??????????????ζ??????GM??1??1???????????????????????IGS(the International GPS Service for Geodynamics)??????????7 ns??????  相似文献   

7.
????T/P(TOPEX/POSEIDON)????????????????????????????????????T/P?????????????????????????????????????????????????????????У??????С????????????????????????????????????????????????????Ч??????T/P?????Ч???????0.3m??????T/P????????Jason??1?????????????????????????????????????????????????????????????????????????????????????????????????????á?T/P??Jason??1????????????????Ч?????????????????????????0.21 m??0.05 m??  相似文献   

8.
???????Envisat??????????????2004??7??12???2005??4??8?????????Ms6.7??Ms6.5?????InSAR????α??????????????ε????????????20 km??20 km??Χ???EW?????????Σ??????η???19.0 cm??30.5 cm???????????????????????????ε???????????????????????,????λ??83.71??E,30.70??N,??Mw6.1,83.72??,E30.52??N????Mw6.2??????????????? 1 m??1.4 m?????ε??????????NW?????3?????????????NS?????????-????????????λ  相似文献   

9.
????·??Ч??????????????????????·??Ч?????????????????????????????????????????·??Ч?????г????????????????????????????????????????????????????б????о????????????????????????г?????????·??Ч????з?????????е????????????????????г????????  相似文献   

10.
??????????????????·??GPS????????????????1 000 kV?????????·?????????????·?????????????????????·??????????????????£?????GPS?????????????????????GPS???????й????????TEQC????????????????????μ?????????P1??P2??·????L1??L2????????????????????????GPS????????????????????????????????????????????·????????λ??GPS????δ?????????????  相似文献   

11.
?????????е???α????????????????λ?????????????????????????????????λ?仯???ɡ?????????????????ж?????????????????????????????α?λ?????н??е??????????GM(1,1)?????????????????????÷??????????????????????÷??????????????GM(1,1)?????????????Ч???????????????  相似文献   

12.
针对现有改进GM(1,1)模型在导航卫星钟差预报中性能无明显提升的问题,提出通过优化初始条件来提高钟差预报精度的方法。首先构建初始条件未知的GM(1,1)预报模型,然后采用原始序列的最新分量求解初始条件,最后利用该模型对IGS提供的精密钟差数据进行预报实验。结果表明,将初始条件优化后的GM(1,1)模型用于钟差预报切实可行,且预报精度比传统GM(1,1)模型有较大提高。  相似文献   

13.
????GM(1,1)???????????????????о????????????????x(1)(1)??x(1)(n)??????????GM(1,1)??????????????????x(1)(1)??x(1)(n)?GM(1,1)????????????·???????x(1)(t)?????????????????1-AGO???е???????????С?????????????????????????????????????????????????????????????????з?????????????????????????????÷?Χ?????????????????????????????????????GM(1,1)????????????????????GM(1,1)????  相似文献   

14.
结合加权非等距GM(1,1)模型与线性回归理论,构建灰线性加权非等距GM(1,1)预测模型,并给出对模型预测精度起决定性作用的灰指数v和参数m的优化方法。与加权非等距GM(1,1)模型和线性回归预测模型相比,灰线性加权非等距GM(1,1)预测模型的精度更高,预测有效时间更长,模型的稳定性更好。优化v和m后,灰线性加权非等距GM(1,1)预测模型的实用性、稳定性进一步提高。  相似文献   

15.
????GM(1,1)?????????????????????????????????????????GM(1,1)?????????????????????????GM(1,1) ??????GM(1,1)??PGM(1,1)?????GM(1,1)????????????б???????????????????????GM(1,1)????????????  相似文献   

16.
地球极移参数高精度双差分LS+AR预报方法研究   总被引:1,自引:0,他引:1  
提出基于双差分最小二乘LS+AR模型的高精度极移参数预报方法。首先,对极移数据进行双差分处理,用以增强数据平稳性,获取差分极移数据,并采用LS方法对差分极移数据进行拟合,获取极移残差数据;其次,利用AR模型对极移残差数据进行预报;然后,综合LS外推预报值与AR模型预报值获取差分极移预报值;最后,对差分极移预报结果进行逆双差分处理,获取高精度的极移预报值。将该方法应用于实际极移参数预报中,结果表明,1d的极移X分量(PMX)预报精度优于0.25mas,极移Y分量(PMY)预报精度优于0.2mas。将该预报结果与国际EOP_PCC预报结果对比表明,极移短期预报精度与EOP_PCC预报结果相当,1d的预报精度略优于EOP_PCC预报结果。  相似文献   

17.
Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.  相似文献   

18.
利用白鹤滩和乌东德库区2018~2019年两期最新地壳形变监测资料对两个库区在监视期的形变特征进行分析,其中水准和重力资料采用相对基准分析法,谷宽和跨断层测距资料采用投影面相对坐标分析法。结果表明:1)白鹤滩库区上游左岸中部存在16 km范围的沉降区,乌东德库区上游右岸水准支线所在地区隆升较大,两个库区其他地区均相对稳定,垂直形变量均小于5 mm;2)两个库区重力场变化基本平稳,无显著性异常变化,个别测点重力值变化较大是周围环境改变导致;3)两个库区4个谷宽网各点的相对坐标变化均不大,但4个谷宽网均显示相对收缩,量值在1~2 mm;4)两个库区6处跨断层场地中有5处比较稳定,监视期间断层无显著垂直活动和水平活动迹象,乌东德库区洛佐场地监视区断层两侧存在一定的差异性垂向运动并伴随水平向挤压运动。该结果可为水库蓄水后形变以及水库诱发地震的研究提供背景参考。  相似文献   

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