Angular measuring system is the most important component of a servo turntable in inertial test apparatus. Its function and precision determine the turntable＇ s function and precision. It attaches importance to resear...Angular measuring system is the most important component of a servo turntable in inertial test apparatus. Its function and precision determine the turntable＇ s function and precision. It attaches importance to research on inertial test equipment. This paper introduces the principle of the angular measuring system using amplitude discrimination mode. The dynamic errors axe analyzed from the aspects of inductosyn, amplitude and function error of double-phase voltage and wavefonn distortion. Through detailed calculation, theory is provided for practical application; system errors are allocated and the angular measuring system meets the accuracy requirement. As a result, the schedule of the angular measuring system can be used in practice.展开更多
Method of testing for dynamic output forces from jet elements is studied, the handwidth is large in testing with this method. By establishing a model of the test system and simulating it, principles of how inherent fe...Method of testing for dynamic output forces from jet elements is studied, the handwidth is large in testing with this method. By establishing a model of the test system and simulating it, principles of how inherent features of the test system affect the dynamic force test are found out. Thus a theoretical foundation is given for the design and error modification to the actual test system.展开更多
In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can eff...In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.展开更多
The objective of this work is to model statistically the ultraviolet radiation index (UV Index) to make forecast (extrapolate) and analyze trends. The task is relevant, due to increased UV flux and high rate of cases ...The objective of this work is to model statistically the ultraviolet radiation index (UV Index) to make forecast (extrapolate) and analyze trends. The task is relevant, due to increased UV flux and high rate of cases non-melanoma skin cancer in northeast of Brazil. The methodology utilized an Autoregressive Distributed Lag model (ADL) or Dynamic Linear Regression model. The monthly data of UV index were measured in east coast of the Brazilian Northeast (City of Natal-Rio Grande do Norte). The Total Ozone is single explanatory variable to model and was obtained from the TOMS and OMI/AURA instruments. The Predictive Mean Matching (PMM) method was used to complete the missing data of UV Index. The results mean squared error (MSE) between the observed UV index and interpolated data by model was of 0.36 and for extrapolation was of 0.30 with correlations of 0.90 and 0.91 respectively. The forecast/extrapolation performed by model for a climatological period (2012-2042) indicated a trend of increased UV (Seasonal Man-Kendall test scored τ = 0.955 and p-value 0.001) if the Total Ozone remain on this tendency to reduce. In those circumstances, the model indicated an increase of almost one unit of UV index to year 2042.展开更多
Based on NCEP/NCAR daily reanalysis data, climate trend rate and other methods are used to quantitatively analyze the change trend of China's summer observed temperature in 1983—2012. Moreover, a dynamics-statist...Based on NCEP/NCAR daily reanalysis data, climate trend rate and other methods are used to quantitatively analyze the change trend of China's summer observed temperature in 1983—2012. Moreover, a dynamics-statistics-combined seasonal forecast method with optimal multi-factor portfolio is applied to analyze the impact of this trend on summer temperature forecast. The results show that: in the three decades, the summer temperature shows a clear upward trend under the condition of global warming, especially over South China, East China, Northeast China and Xinjiang Region, and the trend rate of national average summer temperature was 0.27℃ per decade. However, it is found that the current business model forecast(Coupled Global Climate Model) of National Climate Centre is unable to forecast summer warming trends in China, so that the post-processing forecast effect of dynamics-statistics-combined method is relatively poor. In this study, observed temperatures are processed first by removing linear fitting trend, and then adding it after forecast to offset the deficiency of model forecast indirectly. After test, ACC average value in the latest decade was 0.44 through dynamics-statistics-combined independent sample return forecast. The temporal correlation(TCC) between forecast and observed temperature was significantly improved compared with direct forecast results in most regions, and effectively improved the skill of the dynamics-statistics-combined forecast method in seasonal temperature forecast.展开更多
The Dynamic relation mechanism between ZCE cotton futures price and related listed company stock price has been studied based on the metastock historical data in January 1st,2007 to September 1st,2010,Johansen co-inte...The Dynamic relation mechanism between ZCE cotton futures price and related listed company stock price has been studied based on the metastock historical data in January 1st,2007 to September 1st,2010,Johansen co-integration analysis,Vector error correction model,Granger causality test and variance decomposition method.The results indicated that:long-term equilibrium relationship existed between ZCE cotton futures price and Xinsai share stock price while which changed in the same tendency and speed in the long-term.Cotton futures price is the main reason for the changing of Xinsai share stock price.The lead-lag relationship in changing course had been confirmed that existed between ZCE cotton futures price and the Xinsai share stock price.Meanwhile,the forward pass mechanism of price changing information had been found only from the ZCE cotton futures market to the stock market while showing asymmetry.Conclusions of the study can be used for cotton and related corporate to hedge business risks by the cotton price changes.展开更多
水文模型结构不确定性是影响水文预报精度的重要因素,如何量化并降低其影响是当前的研究热点问题.基于动态系统响应曲线方法(dynamic system response curve,DSRC),假设水文模型系统的误差仅来源于模型结构误差,推导模型结构误差与输入...水文模型结构不确定性是影响水文预报精度的重要因素,如何量化并降低其影响是当前的研究热点问题.基于动态系统响应曲线方法(dynamic system response curve,DSRC),假设水文模型系统的误差仅来源于模型结构误差,推导模型结构误差与输入量的变化量之间的数学关系,结合经典概率论,提出了能够分辨模型结构不确定性来源的考虑模型结构不确定性的动态系统响应曲线校正方法(dynamic system response curve method considering the model structure uncertainty,UNDSRC).将该方法应用于大坡岭流域与富水流域检验UNDSRC方法的综合表现,并与DSRC方法进行比较.研究表明:1)在实际流域检验中,UNDSRC方法相较于DSRC方法具有更好的校正效果,校正效果评价系数分别为0.82与0.60;2)DSRC方法在2个实际流域均可以对新安江模型进行有效校正,且校正效果相似;3)UNDSRC方法校正效果优异且稳定,能够适应更复杂的流域下垫面情况,方法对洪峰流量的校正优于对径流深的校正;4)校正精度相同的情况下,UNDSRC方法相较于DSRC方法具有更小的岭系数.展开更多
Based on the hydrodynamic model and the Xinanjiang model, the fiver stage forecasting model has been proposed. But its performance is not satisfactory as applied to estuary areas. River roughness is a sensitive parame...Based on the hydrodynamic model and the Xinanjiang model, the fiver stage forecasting model has been proposed. But its performance is not satisfactory as applied to estuary areas. River roughness is a sensitive parameter in the hydrodynamic model, and its value is related to some substantial uncertainties in the tidal fiver. According to roughness tests, a new method of roughness dynamic correction was developed to improve the performance of the stage model. The method was focused on the usage of observed data for the studied section, and its parameters were analyzed. Nested with the dynamic correction of roughness, the stage model was applied to the tidal reach of the Caoe River. The results demonstrate that the roughness dynamic correction can improve the simulation accuracy of the stage model, and especially has the capacity of reducing the errors at peak stages.展开更多
文摘Angular measuring system is the most important component of a servo turntable in inertial test apparatus. Its function and precision determine the turntable＇ s function and precision. It attaches importance to research on inertial test equipment. This paper introduces the principle of the angular measuring system using amplitude discrimination mode. The dynamic errors axe analyzed from the aspects of inductosyn, amplitude and function error of double-phase voltage and wavefonn distortion. Through detailed calculation, theory is provided for practical application; system errors are allocated and the angular measuring system meets the accuracy requirement. As a result, the schedule of the angular measuring system can be used in practice.
文摘Method of testing for dynamic output forces from jet elements is studied, the handwidth is large in testing with this method. By establishing a model of the test system and simulating it, principles of how inherent features of the test system affect the dynamic force test are found out. Thus a theoretical foundation is given for the design and error modification to the actual test system.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 40575036 and 40325015）.Acknowledgement The authors thank Drs Zhang Pei-Qun and Bao Ming very much for their valuable comments on the present paper.
文摘In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.
文摘The objective of this work is to model statistically the ultraviolet radiation index (UV Index) to make forecast (extrapolate) and analyze trends. The task is relevant, due to increased UV flux and high rate of cases non-melanoma skin cancer in northeast of Brazil. The methodology utilized an Autoregressive Distributed Lag model (ADL) or Dynamic Linear Regression model. The monthly data of UV index were measured in east coast of the Brazilian Northeast (City of Natal-Rio Grande do Norte). The Total Ozone is single explanatory variable to model and was obtained from the TOMS and OMI/AURA instruments. The Predictive Mean Matching (PMM) method was used to complete the missing data of UV Index. The results mean squared error (MSE) between the observed UV index and interpolated data by model was of 0.36 and for extrapolation was of 0.30 with correlations of 0.90 and 0.91 respectively. The forecast/extrapolation performed by model for a climatological period (2012-2042) indicated a trend of increased UV (Seasonal Man-Kendall test scored τ = 0.955 and p-value 0.001) if the Total Ozone remain on this tendency to reduce. In those circumstances, the model indicated an increase of almost one unit of UV index to year 2042.
基金National Natural Science Foundation of China(4157508241530531+1 种基金41605048)Special Scientific Research Project for Public Interest(GYHY201306021)
文摘Based on NCEP/NCAR daily reanalysis data, climate trend rate and other methods are used to quantitatively analyze the change trend of China's summer observed temperature in 1983—2012. Moreover, a dynamics-statistics-combined seasonal forecast method with optimal multi-factor portfolio is applied to analyze the impact of this trend on summer temperature forecast. The results show that: in the three decades, the summer temperature shows a clear upward trend under the condition of global warming, especially over South China, East China, Northeast China and Xinjiang Region, and the trend rate of national average summer temperature was 0.27℃ per decade. However, it is found that the current business model forecast(Coupled Global Climate Model) of National Climate Centre is unable to forecast summer warming trends in China, so that the post-processing forecast effect of dynamics-statistics-combined method is relatively poor. In this study, observed temperatures are processed first by removing linear fitting trend, and then adding it after forecast to offset the deficiency of model forecast indirectly. After test, ACC average value in the latest decade was 0.44 through dynamics-statistics-combined independent sample return forecast. The temporal correlation(TCC) between forecast and observed temperature was significantly improved compared with direct forecast results in most regions, and effectively improved the skill of the dynamics-statistics-combined forecast method in seasonal temperature forecast.
基金Supported by National Social Science Fund (06BTQ017)
文摘The Dynamic relation mechanism between ZCE cotton futures price and related listed company stock price has been studied based on the metastock historical data in January 1st,2007 to September 1st,2010,Johansen co-integration analysis,Vector error correction model,Granger causality test and variance decomposition method.The results indicated that:long-term equilibrium relationship existed between ZCE cotton futures price and Xinsai share stock price while which changed in the same tendency and speed in the long-term.Cotton futures price is the main reason for the changing of Xinsai share stock price.The lead-lag relationship in changing course had been confirmed that existed between ZCE cotton futures price and the Xinsai share stock price.Meanwhile,the forward pass mechanism of price changing information had been found only from the ZCE cotton futures market to the stock market while showing asymmetry.Conclusions of the study can be used for cotton and related corporate to hedge business risks by the cotton price changes.
文摘水文模型结构不确定性是影响水文预报精度的重要因素,如何量化并降低其影响是当前的研究热点问题.基于动态系统响应曲线方法(dynamic system response curve,DSRC),假设水文模型系统的误差仅来源于模型结构误差,推导模型结构误差与输入量的变化量之间的数学关系,结合经典概率论,提出了能够分辨模型结构不确定性来源的考虑模型结构不确定性的动态系统响应曲线校正方法(dynamic system response curve method considering the model structure uncertainty,UNDSRC).将该方法应用于大坡岭流域与富水流域检验UNDSRC方法的综合表现,并与DSRC方法进行比较.研究表明:1)在实际流域检验中,UNDSRC方法相较于DSRC方法具有更好的校正效果,校正效果评价系数分别为0.82与0.60;2)DSRC方法在2个实际流域均可以对新安江模型进行有效校正,且校正效果相似;3)UNDSRC方法校正效果优异且稳定,能够适应更复杂的流域下垫面情况,方法对洪峰流量的校正优于对径流深的校正;4)校正精度相同的情况下,UNDSRC方法相较于DSRC方法具有更小的岭系数.
基金Project supported by the National Natural Science Foundation of China(Grant No.50679024)the Program"Eleven-Five"for Science and Technology of China(Grant No.2006BAC05B02).
文摘Based on the hydrodynamic model and the Xinanjiang model, the fiver stage forecasting model has been proposed. But its performance is not satisfactory as applied to estuary areas. River roughness is a sensitive parameter in the hydrodynamic model, and its value is related to some substantial uncertainties in the tidal fiver. According to roughness tests, a new method of roughness dynamic correction was developed to improve the performance of the stage model. The method was focused on the usage of observed data for the studied section, and its parameters were analyzed. Nested with the dynamic correction of roughness, the stage model was applied to the tidal reach of the Caoe River. The results demonstrate that the roughness dynamic correction can improve the simulation accuracy of the stage model, and especially has the capacity of reducing the errors at peak stages.
