In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,trunca...In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,truncation method and the Yamada-Watanabe approximation technique,we derived the strong Feller property of the solution.展开更多
We establish a new type of backward stochastic differential equations(BSDEs)connected with stochastic differential games(SDGs), namely, BSDEs strongly coupled with the lower and the upper value functions of SDGs, wher...We establish a new type of backward stochastic differential equations(BSDEs)connected with stochastic differential games(SDGs), namely, BSDEs strongly coupled with the lower and the upper value functions of SDGs, where the lower and the upper value functions are defined through this BSDE. The existence and the uniqueness theorem and comparison theorem are proved for such equations with the help of an iteration method. We also show that the lower and the upper value functions satisfy the dynamic programming principle. Moreover, we study the associated Hamilton-Jacobi-Bellman-Isaacs(HJB-Isaacs)equations, which are nonlocal, and strongly coupled with the lower and the upper value functions. Using a new method, we characterize the pair(W, U) consisting of the lower and the upper value functions as the unique viscosity solution of our nonlocal HJB-Isaacs equation. Furthermore, the game has a value under the Isaacs’ condition.展开更多
The Harnack inequality for stochastic differential equation driven by G-Brownian motion with multiplicative noise is derived by means of the coupling by change of measure,which extends the corresponding results derive...The Harnack inequality for stochastic differential equation driven by G-Brownian motion with multiplicative noise is derived by means of the coupling by change of measure,which extends the corresponding results derived in Wang(Probab.Theory Related Fields 109:417–424)under the linear expectation.Moreover,we generalize the gradient estimate under nonlinear expectation appeared in Song(Sci.China Math.64:1093–1108).展开更多
This paper is dedicated to solving high-dimensional coupled FBSDEs with non- Lipschitz diffusion coefficients numerically. Under mild conditions, we provided a posterior estimate of the numerical solution that holds f...This paper is dedicated to solving high-dimensional coupled FBSDEs with non- Lipschitz diffusion coefficients numerically. Under mild conditions, we provided a posterior estimate of the numerical solution that holds for any time duration. This posterior estimate validates the convergence of the recently proposed Deep BSDE method. In addition, we developed a numerical scheme based on the Deep BSDE method and presented numerical examples in financial markets to demonstrate the high performance.展开更多
We investigate a particle system with mean field interaction living in a random environment characterized by a regime-switching process.The switching process is allowed to be dependent on the particle system.The well-...We investigate a particle system with mean field interaction living in a random environment characterized by a regime-switching process.The switching process is allowed to be dependent on the particle system.The well-posedness and various properties of the limit conditional McKean-Vlasov SDEs are studied,and the conditional propagation of chaos is established with explicit estimate of the convergence rate.展开更多
The recently proposed numerical algorithm,deep BSDE method,has shown remarkable performance in solving high-dimensional forward-backward stochastic differential equations(FBSDEs)and parabolic partial differential equa...The recently proposed numerical algorithm,deep BSDE method,has shown remarkable performance in solving high-dimensional forward-backward stochastic differential equations(FBSDEs)and parabolic partial differential equations(PDEs).This article lays a theoretical foundation for the deep BSDE method in the general case of coupled FBSDEs.In particular,a posteriori error estimation of the solution is provided and it is proved that the error converges to zero given the universal approximation capability of neural networks.Numerical results are presented to demonstrate the accuracy of the analyzed algorithm in solving high-dimensional coupled FBSDEs.展开更多
Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China t...Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.展开更多
A gas puff imaging(GPI)diagnostic has been developed and operated on EAST since 2012,and the time-delay estimation(TDE)method is used to derive the propagation velocity of fluctuations from the two-dimensional GPI dat...A gas puff imaging(GPI)diagnostic has been developed and operated on EAST since 2012,and the time-delay estimation(TDE)method is used to derive the propagation velocity of fluctuations from the two-dimensional GPI data.However,with the TDE method it is difficult to analyze the data with fast transient events,such as edge-localized mode(ELM).Consequently,a method called the spatial displacement estimation(SDE)algorithm is developed to estimate the turbulence velocity with high temporal resolution.Based on the SDE algorithm,we make some improvements,including an adaptive median filter and super-resolution technology.After the development of the algorithm,a straight-line movement and a curved-line movement are used to test the accuracy of the algorithm,and the calculated speed agrees well with preset speed.This SDE algorithm is applied to the EAST GPI data analysis,and the derived propagation velocity of turbulence is consistent with that from the TDE method,but with much higher temporal resolution.展开更多
Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take ...Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues.Hence,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue.Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions computing.The simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their lifespan.Compared with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.展开更多
基金Supported by the National Natural Science Foundation of China(11926322)the Fundamental Research Funds for the Central Universities of South-Central MinZu University(CZY22013,3212023sycxjj001)。
文摘In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,truncation method and the Yamada-Watanabe approximation technique,we derived the strong Feller property of the solution.
基金supported by the NSF of China(11071144,11171187,11222110 and 71671104)Shandong Province(BS2011SF010,JQ201202)+4 种基金SRF for ROCS(SEM)Program for New Century Excellent Talents in University(NCET-12-0331)111 Project(B12023)the Ministry of Education of Humanities and Social Science Project(16YJA910003)Incubation Group Project of Financial Statistics and Risk Management of SDUFE
文摘We establish a new type of backward stochastic differential equations(BSDEs)connected with stochastic differential games(SDGs), namely, BSDEs strongly coupled with the lower and the upper value functions of SDGs, where the lower and the upper value functions are defined through this BSDE. The existence and the uniqueness theorem and comparison theorem are proved for such equations with the help of an iteration method. We also show that the lower and the upper value functions satisfy the dynamic programming principle. Moreover, we study the associated Hamilton-Jacobi-Bellman-Isaacs(HJB-Isaacs)equations, which are nonlocal, and strongly coupled with the lower and the upper value functions. Using a new method, we characterize the pair(W, U) consisting of the lower and the upper value functions as the unique viscosity solution of our nonlocal HJB-Isaacs equation. Furthermore, the game has a value under the Isaacs’ condition.
文摘The Harnack inequality for stochastic differential equation driven by G-Brownian motion with multiplicative noise is derived by means of the coupling by change of measure,which extends the corresponding results derived in Wang(Probab.Theory Related Fields 109:417–424)under the linear expectation.Moreover,we generalize the gradient estimate under nonlinear expectation appeared in Song(Sci.China Math.64:1093–1108).
基金the EPSRC Centre for Doctoral Training in Mathematics of Random Systems:Analysis,Modelling,and Simulation(Grant No.EP/S023925/1).
文摘This paper is dedicated to solving high-dimensional coupled FBSDEs with non- Lipschitz diffusion coefficients numerically. Under mild conditions, we provided a posterior estimate of the numerical solution that holds for any time duration. This posterior estimate validates the convergence of the recently proposed Deep BSDE method. In addition, we developed a numerical scheme based on the Deep BSDE method and presented numerical examples in financial markets to demonstrate the high performance.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.11771327,11831014).
文摘We investigate a particle system with mean field interaction living in a random environment characterized by a regime-switching process.The switching process is allowed to be dependent on the particle system.The well-posedness and various properties of the limit conditional McKean-Vlasov SDEs are studied,and the conditional propagation of chaos is established with explicit estimate of the convergence rate.
文摘The recently proposed numerical algorithm,deep BSDE method,has shown remarkable performance in solving high-dimensional forward-backward stochastic differential equations(FBSDEs)and parabolic partial differential equations(PDEs).This article lays a theoretical foundation for the deep BSDE method in the general case of coupled FBSDEs.In particular,a posteriori error estimation of the solution is provided and it is proved that the error converges to zero given the universal approximation capability of neural networks.Numerical results are presented to demonstrate the accuracy of the analyzed algorithm in solving high-dimensional coupled FBSDEs.
基金supported by the National Natural Science Foundation of China(72373117)the Chinese Universities Scientific Fund(Z1010422003)+1 种基金the Major Project of the Key Research Base of Humanities and Social Sciences of the Ministry of Education(22JJD790052)the Qinchuangyuan Project of Shaanxi Province(QCYRCXM-2022-145).
文摘Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.
基金supported by the National Magnetic Confinement Fusion Energy R&D Program of China(Nos.2022YFE03030001,2022YFE03020004 and 2022YFE 03050003)National Natural Science Foundation of China(Nos.12275310,11975275,12175277 and 11975271)+2 种基金the Science Foundation of Institute of Plasma Physics,Chinese Academy of Sciences(No.DSJJ-2021-01)the Collaborative Innovation Program of Hefei Science Center,Chinese Academy of Sciences(No.2021HSC-CIP019)the Users with Excellence Program of Hefei Science Center,Chinese Academy of Sciences(Nos.2021HSC-UE014 and 2021HSCUE012)。
文摘A gas puff imaging(GPI)diagnostic has been developed and operated on EAST since 2012,and the time-delay estimation(TDE)method is used to derive the propagation velocity of fluctuations from the two-dimensional GPI data.However,with the TDE method it is difficult to analyze the data with fast transient events,such as edge-localized mode(ELM).Consequently,a method called the spatial displacement estimation(SDE)algorithm is developed to estimate the turbulence velocity with high temporal resolution.Based on the SDE algorithm,we make some improvements,including an adaptive median filter and super-resolution technology.After the development of the algorithm,a straight-line movement and a curved-line movement are used to test the accuracy of the algorithm,and the calculated speed agrees well with preset speed.This SDE algorithm is applied to the EAST GPI data analysis,and the derived propagation velocity of turbulence is consistent with that from the TDE method,but with much higher temporal resolution.
基金supported by Basic Science Research Program through the National Natural Science Foundation of China(Grant No.61867003)Key Project of Science and Technology Research and Development Plan of China Railway Co.,Ltd.(N2022X009).
文摘Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues.Hence,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue.Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions computing.The simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their lifespan.Compared with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.
