The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or schedu...The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or scheduling,and integer partitions.An accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical computers.To effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk.The proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum resources.The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era.We investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the model.Moreover,we also discuss the performance of the model under different conditional values at risk.Through computer simulation,the scale can reach more than nine qubits.By selecting the noise type,we construct simulators with different QVs and study the performance of the model with them.In addition,we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem.This model provides a new perspective for solving the subset sum problem.展开更多
In recent years,with the rapid development of China’s economy,a large number of people have flocked to the cities,which also brings more residential waste.The increased waste overloads transfer stations located near ...In recent years,with the rapid development of China’s economy,a large number of people have flocked to the cities,which also brings more residential waste.The increased waste overloads transfer stations located near residential areas,and the continuous noise and odour affect the daily lives of nearby residents.In addition,the neighbourhood avoidance facilities represented by the waste transfer stations also reduce the value of the surrounding residents’houses.Therefore,using the conditional value method and the Tobit and Double Hurder econometric models,this article investigates the implicit value of the Fuli Resort neighbourhood under the influence of the waste transfer station through a questionnaire survey on the willingness of the residents to accept the compensation,which can be regarded as the“aversion value”of the neighbourhood due to the aversion to the waste transfer station and analyses the impact of the aversion value of the neighbourhood.aversion value and analyses the impact on residents’willingness to accept compensation.The study found that the residents’willingness to accept compensation near the waste transfer station is 511.94 RMB/person/month,and the implicit value of the Fuli Resort neighbourhood under the influence of the waste transfer station in Qinhuai District,Nanjing,Jiangsu Province,China,is 147,950 RMB.The study found that residents are most interested in having the government rectify the waste transfer station and set sanitary standards and work norms.展开更多
To provide genetic information and materials for breeding hybrid japonica rice with wide adaptability and strong competitive advantage of yield, elite alleles and their carrier varieties of growth duration （GD） and ...To provide genetic information and materials for breeding hybrid japonica rice with wide adaptability and strong competitive advantage of yield, elite alleles and their carrier varieties of growth duration （GD） and productive panicle number per plant （PN） were detected. A natural population composed of 94 japonica varieties was phenotyped for the GD, PN and plant height （PH） in two environments. The conditional phenotypic data were transferred by the linear model method in software QGAStation 1.0, and association mapping based on the unconditional and conditional phenotype values of GD and PN was analyzed by using general linear model in software TASSEL. A total of 34 simple sequence repeat （SSR） marker loci associated with GD and PN were detected in the two environments. Among them, 15 were associated with GD, and 19 were associated with PN. Four elite alleles of RM8095-120bp, RM7102-176bp, RM72-170bp and RM72-178bp were associated with GD, and their carrier varieties were Hongmangshajing, Nipponbare, Hongmangshajing and Nannongjing 62401, respectively. These elite alleles from the carrier varieties can shorten GD by 2.03-9.93 d when they were introduced into improved materials. RM72-182bp associated with PN was an elite allele, and its carrier variety was Xiaoqingzhong. It can increase PN by three when introduced into improved materials. Moreover, these elite alleles can be used to improve target traits without influencing another two traits.展开更多
Payment for Ecosystem Services(PES)has been widely acknowledged as an effective tool for mitigating grassland degradation and enhancing ecosystem services provision.However,critical factors,such as herders'willing...Payment for Ecosystem Services(PES)has been widely acknowledged as an effective tool for mitigating grassland degradation and enhancing ecosystem services provision.However,critical factors,such as herders'willingness to accept(WTA)preferences and compensation expectations,are often overlooked,leading to insufficient effectiveness of PES initiatives.This study focused on grassland ecological compensation policy(GECP),quantifying herders'WTA compensation for grassland grazing bans.Through face-to-face surveys and employing the contingent valuation method,we estimated households'WTA for participating in a grassland conservation program to bolster ecosystem service provision.Our findings indicated that herders required an average compensation of 237 CNY mu^(-1)yr^(-1)to engage in the grazing ban program.Notably,herders'environmental awareness positively influenced their willingness to participate,whereas larger family sizes were negatively correlated with WTA.Additionally,herders in better health,with higher livestock incomes or categorized as semi-herders,tended to accept lower compensation levels.These insights are crucial for improving the effectiveness of GECP and provide valuable reference points for similar analyses in economically disadvantaged and ecologically fragile regions.展开更多
This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its gene...This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its generalization error bound is established through the lens of uniform convergence analysis.The CVaR-based MRO can achieve the polynomial decay rate on the excess risk,which extends the generalization analysis associated with the expected risk to the risk-averse case.展开更多
Initial value problem for linear second order ordinary differential equation with small parameter by the first and second derivatives is considered. An exponentially fitted difference scheme with constant fitting fact...Initial value problem for linear second order ordinary differential equation with small parameter by the first and second derivatives is considered. An exponentially fitted difference scheme with constant fitting factors is developed in a uniform mesh, which gives first_order uniform convergence in the sense of discrete maximum norm. Numerical results are also presented.展开更多
The paper deals with the existence of three- solutions for the second- order differential equations with nonlinear boundary value conditions x″=f(t,x,x′) , t∈ [a,b], g1(x(a) ,x′(a) ) =0 , g2 (x(b) ,x′(...The paper deals with the existence of three- solutions for the second- order differential equations with nonlinear boundary value conditions x″=f(t,x,x′) , t∈ [a,b], g1(x(a) ,x′(a) ) =0 , g2 (x(b) ,x′(b) ) =0 , where f :[a,b]× R1× R1→ R1,gi:R1× R1→ R1(i=1 ,2 ) are continuous functions.The methods employed are the coincidence degree theory.As an application,the sufficient conditions under which there are arbitrary odd solutions for the BVP are obtained展开更多
In the poper, the method of separating singularity is applied to study the uniformly difference scheme of a singular perturbation problem for a semilinear ordinary differential equation with mixed boundary value condi...In the poper, the method of separating singularity is applied to study the uniformly difference scheme of a singular perturbation problem for a semilinear ordinary differential equation with mixed boundary value condition. The uniform convergence on small parameter ε of order one for an IVin type difference scheme constructed is proved. At the end of the paper, a numerical example is given. The computing results coincide with the theoretical analysis.展开更多
Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial facto...Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial factors,the geometry of the sensor installation will be close to linear,which makes the localization equation suffer from the pathological problem,and the localization accuracy is greatly reduced.To address this problem,the reasons for the pathological problem are analyzed from the perspective of the objective function residuals and coefficient matrix.The pathological problem is caused by the combined effect of the poorer sensor array and data errors,and its residual isosurface shows a conical distribution,and as the residual value decreases,the apex of the isosurface gradually extends to the far side,and the localization results do not converge.For this reason,an improved regularized Newton downhill localization algorithm is proposed.In this method,firstly,the Newtonian downhill method is improved so that the magnitudes of the seismic source parameters are the same,and the condition number of the coefficient matrix is reduced;then,the L-curve method is used to calculate the regularization factor for the pathological equations,and the coefficient matrix is improved;finally,the pathological equations are regularized,and the seismic source coordinates are obtained by the improved Newtonian downhill method.The results of engineering applications show that compared with the traditional algorithm based on automatic of P-arrival picking,the number of effective microseismic events calculated by the proposed localization algorithm is increased by 194.7%,and the localization accuracy is substantially improved.The proposed algorithm reduces the problem of low accuracy of S-arrival picking and allows localization using only P-wave arrival.The method reduces the quality requirements of the data and significantly improves the utilization of microseismic events and positioning accuracy.展开更多
A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC...A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.展开更多
The global financial crisis （GFC） has placed the creditworthiness of banks under intense scrutiny. In particular, capital adequacy has been called into question. Current capital requirements make no allowance for ca...The global financial crisis （GFC） has placed the creditworthiness of banks under intense scrutiny. In particular, capital adequacy has been called into question. Current capital requirements make no allowance for capital erosion caused by movements in the market value of assets. This paper examines default probabilities of Swiss banks under extreme conditions using structural modeling techniques. Conditional Value at Risk （CVaR） and Conditional Probability of Default （CPD） techniques are used to measure capital erosion. Significant increase in Probability of Default （PD） is found during the GFC period. The market asset value based approach indicates a much higher PD than external ratings indicate. Capital adequacy recommendations are formulated which distinguish between real and nominal capital based on asset fluctuations.展开更多
In this paper,based on physics-informed neural networks(PINNs),a good deep learning neural network framework that can be used to effectively solve the nonlinear evolution partial differential equations(PDEs)and other ...In this paper,based on physics-informed neural networks(PINNs),a good deep learning neural network framework that can be used to effectively solve the nonlinear evolution partial differential equations(PDEs)and other types of nonlinear physical models,we study the nonlinear Schrodinger equation(NLSE)with the generalized PT-symmetric Scarf-Ⅱpotential,which is an important physical model in many fields of nonlinear physics.Firstly,we choose three different initial values and the same Dinchlet boundaiy conditions to solve the NLSE with the generalized PT-symmetric Scarf-Ⅱpotential via the PINN deep learning method,and the obtained results are compared with ttose denved by the toditional numencal methods.Then,we mvestigate effect of two factors(optimization steps and activation functions)on the performance of the PINN deep learning method in the NLSE with the generalized PT-symmetric Scarf-Ⅱpotential.Ultimately,the data-driven coefficient discovery of the generalized PT-symmetric Scarf-Ⅱpotential or the dispersion and nonlinear items of the NLSE with the generalized PT-symmetric Scarf-Ⅱpotential can be approximately ascertained by using the PINN deep learning method.Our results may be meaningful for further investigation of the nonlinear Schrodmger equation with the generalized PT-symmetric Scarf-Ⅱpotential in the deep learning.展开更多
The virtual power plant(VPP)facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources(DERs),offering as a potential resource for...The virtual power plant(VPP)facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources(DERs),offering as a potential resource for frequency regulation to enhance the power system flexibility.To fully exploit the flexibility of DER and enhance the revenue of VPP,this paper proposes a multi-temporal optimization strategy of VPP in the energy-frequency regulation(EFR)market under the uncertainties of wind power(WP),photovoltaic(PV),and market price.Firstly,all schedulable electric vehicles(EVs)are aggregated into an electric vehicle cluster(EVC),and the schedulable domain evaluation model of EVC is established.A day-ahead energy bidding model based on Stackelberg game is also established for VPP and EVC.Secondly,on this basis,the multi-temporal optimization model of VPP in the EFR market is proposed.To manage risks stemming from the uncertainties of WP,PV,and market price,the concept of conditional value at risk(CVaR)is integrated into the strategy,effectively balancing the bidding benefits and associated risks.Finally,the results based on operational data from a provincial electricity market demonstrate that the proposed strategy enhances comprehensive revenue by providing frequency regulation services and encouraging EV response scheduling.展开更多
We consider the problem of optimal bidding and portfolio optimization for bidders in the financial transmission rights(FTR)auction market.Based on the price-taker assumption,each FTR market participant aims to maximiz...We consider the problem of optimal bidding and portfolio optimization for bidders in the financial transmission rights(FTR)auction market.Based on the price-taker assumption,each FTR market participant aims to maximize the profit,which is the difference between the clearing price and FTR revenue.However,both clearing price and the FTR revenue are random and unknown.An online learning methodology is proposed to learn optimal bidding by updating its policy with the newest observations of clearing results.With bidding prices derived by the online learning algorithm,a budget-constrained portfolio optimization problem is solved to distribute the budget among profitable FTRs.Compared to other state-of-the-art online learning approaches,the proposed tree-based bid searching(TBS)algorithm converges faster to the optimal bidding price and has favourable linearithmic time complexity.展开更多
In the paper, we consider the existence and uniqueness results for Caputo fractional differential equations with integral boundary value condition. The sufficient conditions of existence and uniqueness are obtained by...In the paper, we consider the existence and uniqueness results for Caputo fractional differential equations with integral boundary value condition. The sufficient conditions of existence and uniqueness are obtained by applying the contraction map-ping principle, Krasnoselskii＇s fixed point theorem and Leray-Schauder degree the-ory, which party improves and extends the associated results of fractional differentialequations. Four examples illustrating our main results are included.展开更多
In the competitive energy market,energy retailers are facing the uncertainties of both energy price and demand,which requires them to formulate reasonable energy purchasing and selling strategies for improving their c...In the competitive energy market,energy retailers are facing the uncertainties of both energy price and demand,which requires them to formulate reasonable energy purchasing and selling strategies for improving their competitiveness in this market.Particularly,the attractive multi-energy retail packages are the key for retailers to increase their benefit.Therefore,combined with incentive means and price signals,five types of multi-energy retail packages such as peak-valley time-of-use(TOU)price package and day-night bundled price package are designed in this paper for retailers.The iterative interactions between retailers and end-users are modeled using a bi-level model of stochastic optimization based on multi-leader multi-follower(MLMF)Stackelberg game,in which retailers are leaders and end-users are followers.Retailers make decisions to maximize the profit considering the conditional value at risk(CVaR)while end-users optimize the satisfaction of both energy comfort and economy.Besides,a distributed algorithm is proposed to obtain the Nash equilibrium of above MLMF Stackelberg game model while the particle swarm optimization(PSO)algorithm and CPLEX solver are applied to solve the optimization model for each participant(retailer or end-user).Numeral results show that the designed retail packages can increase the overall profit of retailers,and the overall satisfaction of industrial users is the highest while that of residential users is the lowest after game interaction.展开更多
In this paper, out main purpose is to establish the existence of nonnegative solu-tions for a class quasilinear ordinary differential equation by modifying the method ofAnuradha et al. [4]. The main results in present...In this paper, out main purpose is to establish the existence of nonnegative solu-tions for a class quasilinear ordinary differential equation by modifying the method ofAnuradha et al. [4]. The main results in present paper are new and extend the resultsof the [4].展开更多
We consider the boundary value problem for the second order quasilinear differential equationwhere f is allowed to change sign, φ(v) = \v\p-2v, p > 1. Using a new fixed point theorem in double cones, we show the e...We consider the boundary value problem for the second order quasilinear differential equationwhere f is allowed to change sign, φ(v) = \v\p-2v, p > 1. Using a new fixed point theorem in double cones, we show the existence of at least two positive solutions of the boundary value problem.展开更多
The paper deals a fractional functional boundary value problems with integral boundary conditions. Besed on the coincidence degree theory, some existence criteria of solutions at resonance are established.
Advanced adiabatic compressed air energy storage(AA-CAES)has the advantages of large capacity,long service time,combined heat and power generation(CHP),and does not consume fossil fuels,making it a promising storage t...Advanced adiabatic compressed air energy storage(AA-CAES)has the advantages of large capacity,long service time,combined heat and power generation(CHP),and does not consume fossil fuels,making it a promising storage technology in a low-carbon society.An appropriate self-scheduling model can guarantee AA-CAES’s profit and attract investments.However,very few studies refer to the cogeneration ability of AA-CAES,which enables the possibility to trade in the electricity and heat markets at the same time.In this paper,we propose a multimarket self-scheduling model to make full use of heat produced in compressors.The volatile market price is modeled by a set of inexact distributions based on historical data through-divergence.Then,the self-scheduling model is cast as a robust risk constrained program by introducing Stackelberg game theory,and equivalently reformulated as a mixed-integer linear program(MILP).The numerical simulation results validate the proposed method and demonstrate that participating in multienergy markets increases overall profits.The impact of uncertainty parameters is also discussed in the sensibility analysis.展开更多
基金supported by the National Key R&D Program of China(Grant No.2019YFA0308700)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301500)。
文摘The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)class.This problem is widely used in encryption,planning or scheduling,and integer partitions.An accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical computers.To effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk.The proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum resources.The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era.We investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the model.Moreover,we also discuss the performance of the model under different conditional values at risk.Through computer simulation,the scale can reach more than nine qubits.By selecting the noise type,we construct simulators with different QVs and study the performance of the model with them.In addition,we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem.This model provides a new perspective for solving the subset sum problem.
文摘In recent years,with the rapid development of China’s economy,a large number of people have flocked to the cities,which also brings more residential waste.The increased waste overloads transfer stations located near residential areas,and the continuous noise and odour affect the daily lives of nearby residents.In addition,the neighbourhood avoidance facilities represented by the waste transfer stations also reduce the value of the surrounding residents’houses.Therefore,using the conditional value method and the Tobit and Double Hurder econometric models,this article investigates the implicit value of the Fuli Resort neighbourhood under the influence of the waste transfer station through a questionnaire survey on the willingness of the residents to accept the compensation,which can be regarded as the“aversion value”of the neighbourhood due to the aversion to the waste transfer station and analyses the impact of the aversion value of the neighbourhood.aversion value and analyses the impact on residents’willingness to accept compensation.The study found that the residents’willingness to accept compensation near the waste transfer station is 511.94 RMB/person/month,and the implicit value of the Fuli Resort neighbourhood under the influence of the waste transfer station in Qinhuai District,Nanjing,Jiangsu Province,China,is 147,950 RMB.The study found that residents are most interested in having the government rectify the waste transfer station and set sanitary standards and work norms.
基金supported by the Program of National High Technology Research and Development,Ministry of Science and Technology,China(Grant No.2010AA101301)the Program of Introducing Talents of Discipline to University in China(Grant No.B08025)+1 种基金the Program of Introducing International Advanced Agricultural Science and Technology in China(Grant No.2006-G8[4]-31-1)the Program of Science-Technology Basis and Conditional Platform in China(Grant No.505005)
文摘To provide genetic information and materials for breeding hybrid japonica rice with wide adaptability and strong competitive advantage of yield, elite alleles and their carrier varieties of growth duration （GD） and productive panicle number per plant （PN） were detected. A natural population composed of 94 japonica varieties was phenotyped for the GD, PN and plant height （PH） in two environments. The conditional phenotypic data were transferred by the linear model method in software QGAStation 1.0, and association mapping based on the unconditional and conditional phenotype values of GD and PN was analyzed by using general linear model in software TASSEL. A total of 34 simple sequence repeat （SSR） marker loci associated with GD and PN were detected in the two environments. Among them, 15 were associated with GD, and 19 were associated with PN. Four elite alleles of RM8095-120bp, RM7102-176bp, RM72-170bp and RM72-178bp were associated with GD, and their carrier varieties were Hongmangshajing, Nipponbare, Hongmangshajing and Nannongjing 62401, respectively. These elite alleles from the carrier varieties can shorten GD by 2.03-9.93 d when they were introduced into improved materials. RM72-182bp associated with PN was an elite allele, and its carrier variety was Xiaoqingzhong. It can increase PN by three when introduced into improved materials. Moreover, these elite alleles can be used to improve target traits without influencing another two traits.
基金supported by the National Natural Science Foundation of China(71934003,72322008,and72348003).
文摘Payment for Ecosystem Services(PES)has been widely acknowledged as an effective tool for mitigating grassland degradation and enhancing ecosystem services provision.However,critical factors,such as herders'willingness to accept(WTA)preferences and compensation expectations,are often overlooked,leading to insufficient effectiveness of PES initiatives.This study focused on grassland ecological compensation policy(GECP),quantifying herders'WTA compensation for grassland grazing bans.Through face-to-face surveys and employing the contingent valuation method,we estimated households'WTA for participating in a grassland conservation program to bolster ecosystem service provision.Our findings indicated that herders required an average compensation of 237 CNY mu^(-1)yr^(-1)to engage in the grazing ban program.Notably,herders'environmental awareness positively influenced their willingness to participate,whereas larger family sizes were negatively correlated with WTA.Additionally,herders in better health,with higher livestock incomes or categorized as semi-herders,tended to accept lower compensation levels.These insights are crucial for improving the effectiveness of GECP and provide valuable reference points for similar analyses in economically disadvantaged and ecologically fragile regions.
基金Supported by Education Science Planning Project of Hubei Province(2020GB198)Natural Science Foundation of Hubei Province(2023AFB523).
文摘This paper analyzes the generalization of minimax regret optimization(MRO)under distribution shift.A new learning framework is proposed by injecting the measure of con-ditional value at risk(CVaR)into MRO,and its generalization error bound is established through the lens of uniform convergence analysis.The CVaR-based MRO can achieve the polynomial decay rate on the excess risk,which extends the generalization analysis associated with the expected risk to the risk-averse case.
文摘Initial value problem for linear second order ordinary differential equation with small parameter by the first and second derivatives is considered. An exponentially fitted difference scheme with constant fitting factors is developed in a uniform mesh, which gives first_order uniform convergence in the sense of discrete maximum norm. Numerical results are also presented.
文摘The paper deals with the existence of three- solutions for the second- order differential equations with nonlinear boundary value conditions x″=f(t,x,x′) , t∈ [a,b], g1(x(a) ,x′(a) ) =0 , g2 (x(b) ,x′(b) ) =0 , where f :[a,b]× R1× R1→ R1,gi:R1× R1→ R1(i=1 ,2 ) are continuous functions.The methods employed are the coincidence degree theory.As an application,the sufficient conditions under which there are arbitrary odd solutions for the BVP are obtained
文摘In the poper, the method of separating singularity is applied to study the uniformly difference scheme of a singular perturbation problem for a semilinear ordinary differential equation with mixed boundary value condition. The uniform convergence on small parameter ε of order one for an IVin type difference scheme constructed is proved. At the end of the paper, a numerical example is given. The computing results coincide with the theoretical analysis.
基金the financial support from the National Natural Science Foundation of China(Grant no.42077263).
文摘Microseismic event location is one of the core parameters in microseismic monitoring,and the accuracy of localization will directly affect the effectiveness of engineering applications.However,limited by spatial factors,the geometry of the sensor installation will be close to linear,which makes the localization equation suffer from the pathological problem,and the localization accuracy is greatly reduced.To address this problem,the reasons for the pathological problem are analyzed from the perspective of the objective function residuals and coefficient matrix.The pathological problem is caused by the combined effect of the poorer sensor array and data errors,and its residual isosurface shows a conical distribution,and as the residual value decreases,the apex of the isosurface gradually extends to the far side,and the localization results do not converge.For this reason,an improved regularized Newton downhill localization algorithm is proposed.In this method,firstly,the Newtonian downhill method is improved so that the magnitudes of the seismic source parameters are the same,and the condition number of the coefficient matrix is reduced;then,the L-curve method is used to calculate the regularization factor for the pathological equations,and the coefficient matrix is improved;finally,the pathological equations are regularized,and the seismic source coordinates are obtained by the improved Newtonian downhill method.The results of engineering applications show that compared with the traditional algorithm based on automatic of P-arrival picking,the number of effective microseismic events calculated by the proposed localization algorithm is increased by 194.7%,and the localization accuracy is substantially improved.The proposed algorithm reduces the problem of low accuracy of S-arrival picking and allows localization using only P-wave arrival.The method reduces the quality requirements of the data and significantly improves the utilization of microseismic events and positioning accuracy.
基金Sponsored by the National Natural Science Foundation of China(70571010)
文摘A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.
文摘The global financial crisis （GFC） has placed the creditworthiness of banks under intense scrutiny. In particular, capital adequacy has been called into question. Current capital requirements make no allowance for capital erosion caused by movements in the market value of assets. This paper examines default probabilities of Swiss banks under extreme conditions using structural modeling techniques. Conditional Value at Risk （CVaR） and Conditional Probability of Default （CPD） techniques are used to measure capital erosion. Significant increase in Probability of Default （PD） is found during the GFC period. The market asset value based approach indicates a much higher PD than external ratings indicate. Capital adequacy recommendations are formulated which distinguish between real and nominal capital based on asset fluctuations.
基金supported by the National Natural Science Foundation of China under Grant Nos.11775121,11435005the K.C.Wong Magna Fund of Ningbo University。
文摘In this paper,based on physics-informed neural networks(PINNs),a good deep learning neural network framework that can be used to effectively solve the nonlinear evolution partial differential equations(PDEs)and other types of nonlinear physical models,we study the nonlinear Schrodinger equation(NLSE)with the generalized PT-symmetric Scarf-Ⅱpotential,which is an important physical model in many fields of nonlinear physics.Firstly,we choose three different initial values and the same Dinchlet boundaiy conditions to solve the NLSE with the generalized PT-symmetric Scarf-Ⅱpotential via the PINN deep learning method,and the obtained results are compared with ttose denved by the toditional numencal methods.Then,we mvestigate effect of two factors(optimization steps and activation functions)on the performance of the PINN deep learning method in the NLSE with the generalized PT-symmetric Scarf-Ⅱpotential.Ultimately,the data-driven coefficient discovery of the generalized PT-symmetric Scarf-Ⅱpotential or the dispersion and nonlinear items of the NLSE with the generalized PT-symmetric Scarf-Ⅱpotential can be approximately ascertained by using the PINN deep learning method.Our results may be meaningful for further investigation of the nonlinear Schrodmger equation with the generalized PT-symmetric Scarf-Ⅱpotential in the deep learning.
基金supported in part by the National Natural Science Foundation of China(No.52477115)(Shanxi)Regional Innovation and Development Joint Fund Project(No.U21A600003).
文摘The virtual power plant(VPP)facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources(DERs),offering as a potential resource for frequency regulation to enhance the power system flexibility.To fully exploit the flexibility of DER and enhance the revenue of VPP,this paper proposes a multi-temporal optimization strategy of VPP in the energy-frequency regulation(EFR)market under the uncertainties of wind power(WP),photovoltaic(PV),and market price.Firstly,all schedulable electric vehicles(EVs)are aggregated into an electric vehicle cluster(EVC),and the schedulable domain evaluation model of EVC is established.A day-ahead energy bidding model based on Stackelberg game is also established for VPP and EVC.Secondly,on this basis,the multi-temporal optimization model of VPP in the EFR market is proposed.To manage risks stemming from the uncertainties of WP,PV,and market price,the concept of conditional value at risk(CVaR)is integrated into the strategy,effectively balancing the bidding benefits and associated risks.Finally,the results based on operational data from a provincial electricity market demonstrate that the proposed strategy enhances comprehensive revenue by providing frequency regulation services and encouraging EV response scheduling.
基金supported in part by the National Key R&D Program of China(2020YFB090600,2020YFB0906005).
文摘We consider the problem of optimal bidding and portfolio optimization for bidders in the financial transmission rights(FTR)auction market.Based on the price-taker assumption,each FTR market participant aims to maximize the profit,which is the difference between the clearing price and FTR revenue.However,both clearing price and the FTR revenue are random and unknown.An online learning methodology is proposed to learn optimal bidding by updating its policy with the newest observations of clearing results.With bidding prices derived by the online learning algorithm,a budget-constrained portfolio optimization problem is solved to distribute the budget among profitable FTRs.Compared to other state-of-the-art online learning approaches,the proposed tree-based bid searching(TBS)algorithm converges faster to the optimal bidding price and has favourable linearithmic time complexity.
文摘In the paper, we consider the existence and uniqueness results for Caputo fractional differential equations with integral boundary value condition. The sufficient conditions of existence and uniqueness are obtained by applying the contraction map-ping principle, Krasnoselskii＇s fixed point theorem and Leray-Schauder degree the-ory, which party improves and extends the associated results of fractional differentialequations. Four examples illustrating our main results are included.
基金supported by the National Natural Science Foundation of China(No.52077146)the Sichuan Science and Technology Program(No.2023YFSY0032).
文摘In the competitive energy market,energy retailers are facing the uncertainties of both energy price and demand,which requires them to formulate reasonable energy purchasing and selling strategies for improving their competitiveness in this market.Particularly,the attractive multi-energy retail packages are the key for retailers to increase their benefit.Therefore,combined with incentive means and price signals,five types of multi-energy retail packages such as peak-valley time-of-use(TOU)price package and day-night bundled price package are designed in this paper for retailers.The iterative interactions between retailers and end-users are modeled using a bi-level model of stochastic optimization based on multi-leader multi-follower(MLMF)Stackelberg game,in which retailers are leaders and end-users are followers.Retailers make decisions to maximize the profit considering the conditional value at risk(CVaR)while end-users optimize the satisfaction of both energy comfort and economy.Besides,a distributed algorithm is proposed to obtain the Nash equilibrium of above MLMF Stackelberg game model while the particle swarm optimization(PSO)algorithm and CPLEX solver are applied to solve the optimization model for each participant(retailer or end-user).Numeral results show that the designed retail packages can increase the overall profit of retailers,and the overall satisfaction of industrial users is the highest while that of residential users is the lowest after game interaction.
基金Supported by Natural Science Foundations of the Committee on Science and Technology of HenanProvince(984050400).
文摘In this paper, out main purpose is to establish the existence of nonnegative solu-tions for a class quasilinear ordinary differential equation by modifying the method ofAnuradha et al. [4]. The main results in present paper are new and extend the resultsof the [4].
基金The project is supported by the National Natural Science Foundation of China(19871005)the Scientific Research Foundation of the Education Department of Hebei Province(2001111).
文摘We consider the boundary value problem for the second order quasilinear differential equationwhere f is allowed to change sign, φ(v) = \v\p-2v, p > 1. Using a new fixed point theorem in double cones, we show the existence of at least two positive solutions of the boundary value problem.
基金Supported by the Fundamental Research Funds for the Central Universities
文摘The paper deals a fractional functional boundary value problems with integral boundary conditions. Besed on the coincidence degree theory, some existence criteria of solutions at resonance are established.
基金supported in part by National Key R&D Program of China(2020YFD1100500)National Natural Science Foundation of China(under Grant 51621065 and 51807101)in part by State Grid Anhui Electric Power Co.,Ltd.Science and Technology Project“Research on grid-connected operation and market mechanism of compressed air energy storage”under Grant 521205180021.
文摘Advanced adiabatic compressed air energy storage(AA-CAES)has the advantages of large capacity,long service time,combined heat and power generation(CHP),and does not consume fossil fuels,making it a promising storage technology in a low-carbon society.An appropriate self-scheduling model can guarantee AA-CAES’s profit and attract investments.However,very few studies refer to the cogeneration ability of AA-CAES,which enables the possibility to trade in the electricity and heat markets at the same time.In this paper,we propose a multimarket self-scheduling model to make full use of heat produced in compressors.The volatile market price is modeled by a set of inexact distributions based on historical data through-divergence.Then,the self-scheduling model is cast as a robust risk constrained program by introducing Stackelberg game theory,and equivalently reformulated as a mixed-integer linear program(MILP).The numerical simulation results validate the proposed method and demonstrate that participating in multienergy markets increases overall profits.The impact of uncertainty parameters is also discussed in the sensibility analysis.
