This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even br...This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even bring uncertainties to macroeconomic output.Especially in the carbon neutrality context,China's coal market is being reconstructed and responding to imbalances between supply and demand;identifying the CPVSs helps alleviate rising market instability and prevent energy-induced system risk.To achieve this objective,we explore causalities among 938 weekly coal prices reported by different coal-producing areas of China from 2006.9.4 to 2021.7.12 using the transfer entropy method.Then,coal price volatility influence is quantified to identify the CPVSs by conjointly using complex network theory and a rank aggregation method.The validity test demonstrates that the proposed hybrid method efficiently identifies the CPVSs as it correlates to many price determinants,e.g.,electricity and coal consumption and generation.The empirical results show that causalities among coal prices changed dramatically in 2016,2018,and 2020,affected by coal decapacity and carbon neutrality policies.Before 2018,coal-producing provinces with strong demand for coal and electricity,e.g.,Jiangxi,Chongqing,and Sichuan,were CPVSs;after 2019,those with comparative advantages in coal supply,e.g.,Gansu and Ningxia,were CPVSs.Overall,the coal market is unstable and sensitive to energy policy and external shocks.Policymakers and market participants are recommended to monitor and manage the CPVSs to improve energy security,avoid policy-induced instability and prevent risks caused by coal price fluctuations.展开更多
In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal s...In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency.展开更多
Heat transfer and entropy generation of developing laminar forced convection flow of water-Al_2O_3 nanofluid in a concentric annulus with constant heat flux on the walls is investigated numerically. In order to determ...Heat transfer and entropy generation of developing laminar forced convection flow of water-Al_2O_3 nanofluid in a concentric annulus with constant heat flux on the walls is investigated numerically. In order to determine entropy generation of fully developed flow, two approaches are employed and it is shown that only one of these methods can provide appropriate results for flow inside annuli. The effects of concentration of nanoparticles, Reynolds number and thermal boundaries on heat transfer enhancement and entropy generation of developing laminar flow inside annuli with different radius ratios and same cross sectional areas are studied. The results show that radius ratio is a very important decision parameter of an annular heat exchanger such that in each Re, there is an optimum radius ratio to maximize Nu and minimize entropy generation. Moreover, the effect of nanoparticles concentration on heat transfer enhancement and minimizing entropy generation is stronger at higher Reynolds.展开更多
The current investigation aims to explore the combined effects of heat and mass transfer on free convection of Sodium alginate-Fe_(3)O_(4) based Brinkmann type nanofluid flow over a vertical rotating frame.The Tiwari ...The current investigation aims to explore the combined effects of heat and mass transfer on free convection of Sodium alginate-Fe_(3)O_(4) based Brinkmann type nanofluid flow over a vertical rotating frame.The Tiwari and Das nanofluid model is employed to examine the effects of dimensionless numbers,including Grashof,Eckert,and Schmidt numbers and governing parameters like solid volume fraction of nanoparticles,Hall current,magnetic field,viscous dissipation,and the chemical reaction on the physical quantities.The dimensionless nonlinear partial differential equations are solved using a finite difference method known as Runge-Kutta Fehlberg(RKF-45)method.The variation of dimensionless velocity,temperature,concentration,skin friction,heat,and mass transfer rate,as well as for entropy generation and Bejan number with governing parameters,are presented graphically and are provided in tabular form.The results reveal that the Nusselt number increases with an increase in the solid volume fraction of nanoparticles.Furthermore,the rate of entropy generation and Bejan number depends upon the magnetic field and the Eckert number.展开更多
Correlations between two time series,including the linear Pearson correlation and the nonlinear transfer entropy,have attracted significant attention.In this work,we studied the correlations between multiple stock dat...Correlations between two time series,including the linear Pearson correlation and the nonlinear transfer entropy,have attracted significant attention.In this work,we studied the correlations between multiple stock data with the introduction of a time delay and a rolling window.In most cases,the Pearson correlation and transfer entropy share the same tendency,where a higher correlation provides more information for predicting future trends from one stock to another,but a lower correlation provides less.Considering the computational complexity of the transfer entropy and the simplicity of the Pearson correlation,using the linear correlation with time delays and a rolling window is a robust and simple method to quantify the mutual information between stocks.Predictions made by the long short-term memory method with mutual information outperform those made only with selfinformation when there are high correlations between two stocks.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72401207 and 42101300)Beijing Municipal Education Commission,China(Grant No.SM202110038001).
文摘This paper investigates China's coal price volatility spreaders(CPVSs)from the supply side to locate the volatility source since coal price volatility may destabilize many downstream products'prices or even bring uncertainties to macroeconomic output.Especially in the carbon neutrality context,China's coal market is being reconstructed and responding to imbalances between supply and demand;identifying the CPVSs helps alleviate rising market instability and prevent energy-induced system risk.To achieve this objective,we explore causalities among 938 weekly coal prices reported by different coal-producing areas of China from 2006.9.4 to 2021.7.12 using the transfer entropy method.Then,coal price volatility influence is quantified to identify the CPVSs by conjointly using complex network theory and a rank aggregation method.The validity test demonstrates that the proposed hybrid method efficiently identifies the CPVSs as it correlates to many price determinants,e.g.,electricity and coal consumption and generation.The empirical results show that causalities among coal prices changed dramatically in 2016,2018,and 2020,affected by coal decapacity and carbon neutrality policies.Before 2018,coal-producing provinces with strong demand for coal and electricity,e.g.,Jiangxi,Chongqing,and Sichuan,were CPVSs;after 2019,those with comparative advantages in coal supply,e.g.,Gansu and Ningxia,were CPVSs.Overall,the coal market is unstable and sensitive to energy policy and external shocks.Policymakers and market participants are recommended to monitor and manage the CPVSs to improve energy security,avoid policy-induced instability and prevent risks caused by coal price fluctuations.
基金Project supported by the Jiangsu Province Science Foundation,China(Grant No.BK2011759)
文摘In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency.
文摘Heat transfer and entropy generation of developing laminar forced convection flow of water-Al_2O_3 nanofluid in a concentric annulus with constant heat flux on the walls is investigated numerically. In order to determine entropy generation of fully developed flow, two approaches are employed and it is shown that only one of these methods can provide appropriate results for flow inside annuli. The effects of concentration of nanoparticles, Reynolds number and thermal boundaries on heat transfer enhancement and entropy generation of developing laminar flow inside annuli with different radius ratios and same cross sectional areas are studied. The results show that radius ratio is a very important decision parameter of an annular heat exchanger such that in each Re, there is an optimum radius ratio to maximize Nu and minimize entropy generation. Moreover, the effect of nanoparticles concentration on heat transfer enhancement and minimizing entropy generation is stronger at higher Reynolds.
文摘The current investigation aims to explore the combined effects of heat and mass transfer on free convection of Sodium alginate-Fe_(3)O_(4) based Brinkmann type nanofluid flow over a vertical rotating frame.The Tiwari and Das nanofluid model is employed to examine the effects of dimensionless numbers,including Grashof,Eckert,and Schmidt numbers and governing parameters like solid volume fraction of nanoparticles,Hall current,magnetic field,viscous dissipation,and the chemical reaction on the physical quantities.The dimensionless nonlinear partial differential equations are solved using a finite difference method known as Runge-Kutta Fehlberg(RKF-45)method.The variation of dimensionless velocity,temperature,concentration,skin friction,heat,and mass transfer rate,as well as for entropy generation and Bejan number with governing parameters,are presented graphically and are provided in tabular form.The results reveal that the Nusselt number increases with an increase in the solid volume fraction of nanoparticles.Furthermore,the rate of entropy generation and Bejan number depends upon the magnetic field and the Eckert number.
文摘Correlations between two time series,including the linear Pearson correlation and the nonlinear transfer entropy,have attracted significant attention.In this work,we studied the correlations between multiple stock data with the introduction of a time delay and a rolling window.In most cases,the Pearson correlation and transfer entropy share the same tendency,where a higher correlation provides more information for predicting future trends from one stock to another,but a lower correlation provides less.Considering the computational complexity of the transfer entropy and the simplicity of the Pearson correlation,using the linear correlation with time delays and a rolling window is a robust and simple method to quantify the mutual information between stocks.Predictions made by the long short-term memory method with mutual information outperform those made only with selfinformation when there are high correlations between two stocks.
文摘实现储能系统安全运行,对锂离子电池可用容量的准确预测非常关键。通过对储能电池相关参数进行信息熵分析,筛选出对于电池可用容量具有显著影响的健康因子,将信息熵筛选出的健康因子与水母搜索反向传播神经网络(jellyfish search-back propagation neural network,JS-BP)相结合,建立电池可用容量预测模型。基于美国航空航天局(National Aeronautics and Space Administration,NASA)公开的相关老化数据集与电池老化实验平台的老化数据展开综合分析,其结果表明所提模型具有较高的电池容量预测精度,平均绝对误差(mean absolute error,MAE)、均方根误差(root mean square error,RMSE)均处于较低水平,验证了该模型的准确性。
