We investigate realization of the infinite-dimensional 3-algebras in the classical Calogero-Moser model. In terms of the Lax matrix of the Calogero Moser model and the Nambu 3-brackets in which the variables are the c...We investigate realization of the infinite-dimensional 3-algebras in the classical Calogero-Moser model. In terms of the Lax matrix of the Calogero Moser model and the Nambu 3-brackets in which the variables are the coordinates qi, and canonically conjugate momenta pi and the coupling parameter β are an extra auxiliary phase-space parameter, we present the realization of the Virasoro-Witt, w∞ and SDi f f （T2） 3-algebras, respectively.展开更多
An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.Th...An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.展开更多
Determining which variables affect price realized volatility has always been challenging.This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast.T...Determining which variables affect price realized volatility has always been challenging.This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast.The methodological proposal is based on using the best econometric and machine learning models to forecast realized volatility.In particular,the best forecasting from heterogeneous autoregressive and long short-term memory models are used to determine the influence of the Standard and Poor’s 500 index,euro-US dollar exchange rate,price of gold,and price of Brent crude oil on the realized volatility of natural gas.These financial assets influenced the realized volatility of natural gas in 87.4% of the days analyzed;the euro-US dollar exchange rate was the primary financial asset and explained 40.1% of the influence.The results of the proposed daily analysis differed from those of the methodology used to study the entire period.The traditional model,which studies the entire period,cannot determine temporal effects,whereas the proposed methodology can.The proposed methodology allows us to distinguish the effects for each day,week,or month rather than averages for entire periods,with the flexibility to analyze different frequencies and periods.This methodological capability is key to analyzing influences and making decisions about realized volatility.展开更多
This study evaluates the predictive accuracy of traditional time series(TS)models versus machine learning(ML)methods in forecasting realized volatility across major cryptocurrencies—Bitcoin(BTC),Ethereum(ETH),Litecoi...This study evaluates the predictive accuracy of traditional time series(TS)models versus machine learning(ML)methods in forecasting realized volatility across major cryptocurrencies—Bitcoin(BTC),Ethereum(ETH),Litecoin(LTC),and Ripple(XRP).Employing high-frequency data,we analyze cross-cryptocurrency volatility dynamics through two complementary approaches:volatility forecasting and connectedness analysis.Our findings reveal three key insights:(i)TS models,particularly the heterogeneous autoregressive(HAR)model,exhibit superior predictive performance over their ML counterparts,with the long short-term memory(LSTM)model providing competitive yet inconsistent results due to overfitting and short-term volatility challenges;(ii)including lagged realized volatility of large-cap coins improves predictive accuracy for mid-cap coins,especially XRP,whereas forecasts for largecap coins remain stable,indicating more resilient volatility patterns;and(iii)volatility connectedness analysis reveals substantial spillover effects,particularly pronounced during market turmoil,with large-cap assets(BTC and ETH)acting as primary volatility transmitters and mid-cap assets(XRP and LTC)serving as volatility receivers.These results contribute to the understanding of volatility forecasting and risk management in cryptocurrency markets,offering implications for investors and policymakers in managing market risk and interdependencies in digital asset portfolios.展开更多
China Geodetic Coordinate System 2000(CGCS2000)has been used for several years as a formal published reference frame.The coordinates of all global navigation satellite system(GNSS)stations in China need to be correcte...China Geodetic Coordinate System 2000(CGCS2000)has been used for several years as a formal published reference frame.The coordinates of all global navigation satellite system(GNSS)stations in China need to be corrected to align with the CGCS2000 frame.Different strategies can be adopted for the realization of an optimal reference frame.However,different strategies lead to different results,with differences as great as several decimeters when GNSS station coordinates are transformed into CGCS2000-defined coordinates.The two common methods for the coordinate correction of a GNSS station are quasi-stable adjustment under CGCS2000 and plate movement correction,and the differences between their results can be greater than 10 cm.In this study,a statistic method called"supervised clustering"is applied to the selection of GNSS reference stations;a new scheme named"partition spacing"for the grouping of all processed GNSS stations is proposed;and the plate movement correction method is used to correct the coordinates of all GNSS stations from the GNSS epoch to the CGCS2000 epoch.The results from the new partitioning method were found to be significantly better than those from the conventional station-blocking approach.When coordinates from the stations without grouping were used as the standard,the accuracy of all the three-dimensional coordinate components from the new partitioning method was better than 2 mm.The root mean squares(RMSs)of the velocities in the x,y,and z directions resulting from the supervised clustering method were 0.19,0.45,and 0.32 mm∙a1,respectively,which were much smaller than the values of 0.92,0.72,and 0.97 mm∙a1 that resulted from the conventional approach.In addition,singular spectrum analysis(SSA)was used to model and predict the position nonlinear movements.The modeling accuracies of SSA were better than 3,2,and 5 mm in the east(E),north(N),and up(U)directions,respectively;and its prediction accuracies were better than 5 mm and 1 cm for the horizontal and vertical domains,respectively.展开更多
This paper incorporates the Baidu Index into various heterogeneous autoregressive type time series models and shows that the Baidu Index is a superior predictor of realized volatility in the SSE 50 Index.Furthermore,t...This paper incorporates the Baidu Index into various heterogeneous autoregressive type time series models and shows that the Baidu Index is a superior predictor of realized volatility in the SSE 50 Index.Furthermore,the predictability of the Baidu Index is found to rise as the forecasting horizon increases.We also find that continuous components enhance predictive power across all horizons,but that increases are only sustained in the short and medium terms,as the long-term impact on volatility is less persistent.Our findings should be expected to influence investors interested in constructing trading strategies based on realized volatility.展开更多
The upper reach of the Yellow River from Daliushu to Shapotou consists of five bends and has complex topography. A two-dimensional Re-Normalisation Group （RNG） k-ε model was developed to simulate the flow in the re...The upper reach of the Yellow River from Daliushu to Shapotou consists of five bends and has complex topography. A two-dimensional Re-Normalisation Group （RNG） k-ε model was developed to simulate the flow in the reach. In order to take the circulation currents in the bends into account, the momentum equations were improved by adding an additional source term. Comparison of the numerical simulation with field measurements indicates that the improved two-dimensional depth-averaged RNG k-e model can improve the accuracy of the numerical simulation. A rapid adaptive algorithm was constructed, which can automatically adjust Manning＇s roughness coefficient in different parts of the study river reach. As a result, not only can the trial computation time be significantly shortened, but the accuracy of the numerical simulation can also be greatly improved. Comparison of the simulated and measured water surface slopes for four typical cases shows that the longitudinal and transverse slopes of the water surface increase with the average velocity upstream. In addition, comparison was made between the positions of the talweg and the main streamline, which coincide for most of the study river reach. However, deviations between the positions of the talweg and the main streamline were found at the junction of two bends, at the position where the river width suddenly decreases or increases.展开更多
This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the la...This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the latter derived from the former. It is confirmed that significant differences exist between uncertainty descriptors, and propagation of uncertainty to end products is immensely affected by the specification of source uncertainty.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 11375119 and 11031005the Beijing Municipal Commission of Education under Grant No KZ201210028032
文摘We investigate realization of the infinite-dimensional 3-algebras in the classical Calogero-Moser model. In terms of the Lax matrix of the Calogero Moser model and the Nambu 3-brackets in which the variables are the coordinates qi, and canonically conjugate momenta pi and the coupling parameter β are an extra auxiliary phase-space parameter, we present the realization of the Virasoro-Witt, w∞ and SDi f f （T2） 3-algebras, respectively.
基金supported by research grants from the Natural Sciences and Engineering Research Council(NSERC)of Canada
文摘An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.
文摘Determining which variables affect price realized volatility has always been challenging.This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast.The methodological proposal is based on using the best econometric and machine learning models to forecast realized volatility.In particular,the best forecasting from heterogeneous autoregressive and long short-term memory models are used to determine the influence of the Standard and Poor’s 500 index,euro-US dollar exchange rate,price of gold,and price of Brent crude oil on the realized volatility of natural gas.These financial assets influenced the realized volatility of natural gas in 87.4% of the days analyzed;the euro-US dollar exchange rate was the primary financial asset and explained 40.1% of the influence.The results of the proposed daily analysis differed from those of the methodology used to study the entire period.The traditional model,which studies the entire period,cannot determine temporal effects,whereas the proposed methodology can.The proposed methodology allows us to distinguish the effects for each day,week,or month rather than averages for entire periods,with the flexibility to analyze different frequencies and periods.This methodological capability is key to analyzing influences and making decisions about realized volatility.
文摘This study evaluates the predictive accuracy of traditional time series(TS)models versus machine learning(ML)methods in forecasting realized volatility across major cryptocurrencies—Bitcoin(BTC),Ethereum(ETH),Litecoin(LTC),and Ripple(XRP).Employing high-frequency data,we analyze cross-cryptocurrency volatility dynamics through two complementary approaches:volatility forecasting and connectedness analysis.Our findings reveal three key insights:(i)TS models,particularly the heterogeneous autoregressive(HAR)model,exhibit superior predictive performance over their ML counterparts,with the long short-term memory(LSTM)model providing competitive yet inconsistent results due to overfitting and short-term volatility challenges;(ii)including lagged realized volatility of large-cap coins improves predictive accuracy for mid-cap coins,especially XRP,whereas forecasts for largecap coins remain stable,indicating more resilient volatility patterns;and(iii)volatility connectedness analysis reveals substantial spillover effects,particularly pronounced during market turmoil,with large-cap assets(BTC and ETH)acting as primary volatility transmitters and mid-cap assets(XRP and LTC)serving as volatility receivers.These results contribute to the understanding of volatility forecasting and risk management in cryptocurrency markets,offering implications for investors and policymakers in managing market risk and interdependencies in digital asset portfolios.
基金This study is supported by the National Key Research and Development Program of China(2016YFB0501405)Natural Resources Innovation Platform Construction and Capacity Improvement(A19090)The Fundamental Research Funds for Chinese Academy of Surveying and Mapping(AR1903 and AR2005).
文摘China Geodetic Coordinate System 2000(CGCS2000)has been used for several years as a formal published reference frame.The coordinates of all global navigation satellite system(GNSS)stations in China need to be corrected to align with the CGCS2000 frame.Different strategies can be adopted for the realization of an optimal reference frame.However,different strategies lead to different results,with differences as great as several decimeters when GNSS station coordinates are transformed into CGCS2000-defined coordinates.The two common methods for the coordinate correction of a GNSS station are quasi-stable adjustment under CGCS2000 and plate movement correction,and the differences between their results can be greater than 10 cm.In this study,a statistic method called"supervised clustering"is applied to the selection of GNSS reference stations;a new scheme named"partition spacing"for the grouping of all processed GNSS stations is proposed;and the plate movement correction method is used to correct the coordinates of all GNSS stations from the GNSS epoch to the CGCS2000 epoch.The results from the new partitioning method were found to be significantly better than those from the conventional station-blocking approach.When coordinates from the stations without grouping were used as the standard,the accuracy of all the three-dimensional coordinate components from the new partitioning method was better than 2 mm.The root mean squares(RMSs)of the velocities in the x,y,and z directions resulting from the supervised clustering method were 0.19,0.45,and 0.32 mm∙a1,respectively,which were much smaller than the values of 0.92,0.72,and 0.97 mm∙a1 that resulted from the conventional approach.In addition,singular spectrum analysis(SSA)was used to model and predict the position nonlinear movements.The modeling accuracies of SSA were better than 3,2,and 5 mm in the east(E),north(N),and up(U)directions,respectively;and its prediction accuracies were better than 5 mm and 1 cm for the horizontal and vertical domains,respectively.
基金This work is supported by the National Natural Science Foundation of China(71790594,71701150,and U1811462).
文摘This paper incorporates the Baidu Index into various heterogeneous autoregressive type time series models and shows that the Baidu Index is a superior predictor of realized volatility in the SSE 50 Index.Furthermore,the predictability of the Baidu Index is found to rise as the forecasting horizon increases.We also find that continuous components enhance predictive power across all horizons,but that increases are only sustained in the short and medium terms,as the long-term impact on volatility is less persistent.Our findings should be expected to influence investors interested in constructing trading strategies based on realized volatility.
基金supported by the National Natural Science Foundation of China(Grants No.11361002 and 91230111)the Natural Science Foundation of Ningxia,China(Grant No.NZ13086)+1 种基金the Project of Beifang University of Nationalities,China(Grant No.2012XZK05)the Foreign Expert Project of Beifang University of Nationalities,China,and the Visiting Scholar Foundation of State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,China(Grant No.2013A011)
文摘The upper reach of the Yellow River from Daliushu to Shapotou consists of five bends and has complex topography. A two-dimensional Re-Normalisation Group （RNG） k-ε model was developed to simulate the flow in the reach. In order to take the circulation currents in the bends into account, the momentum equations were improved by adding an additional source term. Comparison of the numerical simulation with field measurements indicates that the improved two-dimensional depth-averaged RNG k-e model can improve the accuracy of the numerical simulation. A rapid adaptive algorithm was constructed, which can automatically adjust Manning＇s roughness coefficient in different parts of the study river reach. As a result, not only can the trial computation time be significantly shortened, but the accuracy of the numerical simulation can also be greatly improved. Comparison of the simulated and measured water surface slopes for four typical cases shows that the longitudinal and transverse slopes of the water surface increase with the average velocity upstream. In addition, comparison was made between the positions of the talweg and the main streamline, which coincide for most of the study river reach. However, deviations between the positions of the talweg and the main streamline were found at the junction of two bends, at the position where the river width suddenly decreases or increases.
文摘This paper investigates the differences that result from applying different approaches to uncertainty modeling and reports an experimental examining error estimation and propagation in elevation and slope, with the latter derived from the former. It is confirmed that significant differences exist between uncertainty descriptors, and propagation of uncertainty to end products is immensely affected by the specification of source uncertainty.
