In this article, the joint distributions of several actuarial diagnostics which are important to insurers＇ running for the jump-diffusion risk process are examined. They include the ruin time, the time of the surplus...In this article, the joint distributions of several actuarial diagnostics which are important to insurers＇ running for the jump-diffusion risk process are examined. They include the ruin time, the time of the surplus process leaving zero ultimately （simply, the ultimately leaving-time）, the surplus immediately prior to ruin, the supreme profits before ruin, the supreme profits and deficit until it leaves zero ultimately and so on. The explicit expressions for their distributions are obtained mainly by the various properties of Levy process, such as the homogeneous strong Markov property and the spatial homogeneity property etc, moveover, the many properties for Brownian motion.展开更多
The classical Poisson risk model in ruin theory assumed that the interarrival times between two successive claims are mutually independent, and the claim sizes and claim intervals are also mutually independent. In thi...The classical Poisson risk model in ruin theory assumed that the interarrival times between two successive claims are mutually independent, and the claim sizes and claim intervals are also mutually independent. In this paper, we modify the classical Poisson risk model to describe the surplus process of an insurance portfolio. We consider a jump-diffusion risk process compounded by a geometric Brownian motion, and assume that the claim sizes and claim intervals are dependent. Using the properties of conditional expectation, we establish integro-differential equations for the Gerber-Shiu function and the ultimate ruin probability.展开更多
In this paper, the optimal XL-reinsurance of an insurer with jump-diffusion risk process is studied. With the assumptions that the risk process is a compound Possion process perturbed by a standard Brownian motion and...In this paper, the optimal XL-reinsurance of an insurer with jump-diffusion risk process is studied. With the assumptions that the risk process is a compound Possion process perturbed by a standard Brownian motion and the reinsurance premium is calculated according to the variance principle, the implicit expression of the priority and corresponding value function when the utility function is exponential are obtained. At last, the value function is argued, the properties of the priority about parameters are discussed and numerical results of the priority for various claim-size distributions are shown.展开更多
Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure ri...Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.展开更多
A framework for the optimal sparse-control of the probability density function of a jump-diffusion process is presented. This framework is based on the partial integro-differential Fokker-Planck (FP) equation that gov...A framework for the optimal sparse-control of the probability density function of a jump-diffusion process is presented. This framework is based on the partial integro-differential Fokker-Planck (FP) equation that governs the time evolution of the probability density function of this process. In the stochastic process and, correspondingly, in the FP model the control function enters as a time-dependent coefficient. The objectives of the control are to minimize a discrete-in-time, resp. continuous-in-time, tracking functionals and its L2- and L1-costs, where the latter is considered to promote control sparsity. An efficient proximal scheme for solving these optimal control problems is considered. Results of numerical experiments are presented to validate the theoretical results and the computational effectiveness of the proposed control framework.展开更多
Renewable energy sources,including wind,solar,and biofuels,are essential for promoting sustainable economic development and mitigating environmental challenges.As China’s overseas investments in renewable energy expa...Renewable energy sources,including wind,solar,and biofuels,are essential for promoting sustainable economic development and mitigating environmental challenges.As China’s overseas investments in renewable energy expand,effective risk assessment and management have become critical.This study develops a comprehensive risk evaluation framework for China’s overseas renewable energy investments using the Fuzzy Analytic Hierarchy Process(FAHP).The framework incorporates political,economic,and project-specific risks,organized through three primary criteria,nine sub-criteria,and thirty tertiary indicators.By integrating expert judgments with fuzzy set theory,the FAHP methodology assigns accurate weights to risk factors and ensures consistency in evaluation.The findings identify political risks as the most significant,emphasizing their influence on investment strategies.These insights offer valuable guidance for policymakers and investors to enhance risk management strategies and ensure the sustainability of China’s renewable energy initiatives abroad.展开更多
In this paper,a class of risk processes perturbed by diffusion are considered. The Lundberg inequalities for the ruin probability are obtained.The size of the Lundberg exponents for different kinds of risk model is co...In this paper,a class of risk processes perturbed by diffusion are considered. The Lundberg inequalities for the ruin probability are obtained.The size of the Lundberg exponents for different kinds of risk model is compared. The numerical illustration for the impact of the parameters on the ruin probability is given.展开更多
Analysis errors can occur in the desorbing process of ginkgo diterpene lactone meglumine injection(GDMI) by a conventional analysis method, due to several factors, such as easily crystallized samples, solvent volatili...Analysis errors can occur in the desorbing process of ginkgo diterpene lactone meglumine injection(GDMI) by a conventional analysis method, due to several factors, such as easily crystallized samples, solvent volatility, time-consuming sample pre-processing, fixed method, and offline analysis. Based on risk management, near-infrared(NIR) and mid-infrared(MIR) spectroscopy techniques were introduced to solve the above problems with the advantage of timely analysis and non-destructive nature towards samples. The objective of the present study was to identify the feasibility of using NIR or MIR spectroscopy techniques to increase the analysis accuracy of samples from the desorbing process of GDMI. Quantitative models of NIR and MIR were established based on partial least square method and the performances were calculated. Compared to NIR model, MIR model showed greater accuracy and applicability for the analysis of the GDMI desorbing solutions. The relative errors of the concentrations of Ginkgolide A(GA) and Ginkgolide B(GB) were 2.40% and 2.89%, respectively, which were less than 5.00%. The research demonstrated the potential of the MIR spectroscopy technique for the rapid and non-destructive quantitative analysis of the concentrations of GA and GB.展开更多
Seismic risk evaluation(SRE) in early stages(e.g., project planning and preliminary design)for a mountain tunnel located in seismic areas has the same importance as that in final stages(e.g.,performance-based design, ...Seismic risk evaluation(SRE) in early stages(e.g., project planning and preliminary design)for a mountain tunnel located in seismic areas has the same importance as that in final stages(e.g.,performance-based design, structural analysis, and optimization). SRE for planning mountain tunnels bridges the gap between the planning on the macro level and the design/analysis on the micro level regarding the risk management of infrastructural systems. A transition from subjective or qualitative description to objective or quantitative quantification of seismic risk is aimed to improve the seismic behavior of the mountain tunnel and thus reduce the associated seismic risk. A new method of systematic SRE for the planning mountain tunnel was presented herein. The method employs extension theory(ET)and an ET-based improved analytical hierarchy process. Additionally, a new risk-classification criterion is proposed to classify and quantify the seismic risk for a planning mountain tunnel. This SRE method is applied to a mountain tunnel in southwest China, using the extension model based on matter element theory and dependent function operation.The reasonability and flexibility of the SRE method for application to the mountain tunnel are illustrated.According to different seismic risk levels and classification criteria, methods and measures for improving the seismic design are proposed, which can reduce the seismic risk and provide a frame of reference for elaborate seismic design.展开更多
In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(...In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.展开更多
Markov decision processes （MDPs） and their variants are widely studied in the theory of controls for stochastic discrete- event systems driven by Markov chains. Much of the literature focusses on the risk-neutral cr...Markov decision processes （MDPs） and their variants are widely studied in the theory of controls for stochastic discrete- event systems driven by Markov chains. Much of the literature focusses on the risk-neutral criterion in which the expected rewards, either average or discounted, are maximized. There exists some literature on MDPs that takes risks into account. Much of this addresses the exponential utility （EU） function and mechanisms to penalize different forms of variance of the rewards. EU functions have some numerical deficiencies, while variance measures variability both above and below the mean rewards; the variability above mean rewards is usually beneficial and should not be penalized/avoided. As such, risk metrics that account for pre-specified targets （thresholds） for rewards have been considered in the literature, where the goal is to penalize the risks of revenues falling below those targets. Existing work on MDPs that takes targets into account seeks to minimize risks of this nature. Minimizing risks can lead to poor solutions where the risk is zero or near zero, but the average rewards are also rather low. In this paper, hence, we study a risk-averse criterion, in particular the so-called downside risk, which equals the probability of the revenues falling below a given target, where, in contrast to minimizing such risks, we only reduce this risk at the cost of slightly lowered average rewards. A solution where the risk is low and the average reward is quite high, although not at its maximum attainable value, is very attractive in practice. To be more specific, in our formulation, the objective function is the expected value of the rewards minus a scalar times the downside risk. In this setting, we analyze the infinite horizon MDP, the finite horizon MDP, and the infinite horizon semi-MDP （SMDP）. We develop dynamic programming and reinforcement learning algorithms for the finite and infinite horizon. The algorithms are tested in numerical studies and show encouraging performance.展开更多
Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually sin...Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually since it won a contract for a nuclear power plant construction project in the United Arab Emirates in 2009. However, time and monetary resources have been lost in some nuclear power plant construction sites due to lack of risk management ability. The need to prevent losses at nuclear power plant construction sites has become more urgent because it demands professional skills and large-scale resources. Therefore, in this study, the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) were applied in order to make comparisons between decision-making methods, to assess the potential risks at nuclear power plant construction sites. To suggest the appropriate choice between two decision-making methods, a survey was carried out. From the results, the importance and the priority of 24 risk factors, classified by process, cost, safety, and quality, were analyzed. The FAHP was identified as a suitable method for risk assessment of nuclear power plant construction, compared with risk assessment using the AHP. These risk factors will be able to serve as baseline data for risk management in nuclear power plant construction projects.展开更多
This paper studies a Sparre Andersen negative risk sums model in which the distribution of ＂interclaim＂ time is that of a sum of n independent exponential random variables. Thus, the Erlang（n） model is a special c...This paper studies a Sparre Andersen negative risk sums model in which the distribution of ＂interclaim＂ time is that of a sum of n independent exponential random variables. Thus, the Erlang（n） model is a special case. On this basis the correlated negative risk sums process with the common Erlang process is considered. Integro-differential equations with boundary conditions for ψ（u） are given. For some special cases a closed-form expression for ψ（u） is derived.展开更多
This study focused on developing a risk assessment method for explosion at a coal reclaim tunnel （CRT） facility. The method was developed based on an analytical hierarchy process （AHP）, which is an expert system t...This study focused on developing a risk assessment method for explosion at a coal reclaim tunnel （CRT） facility. The method was developed based on an analytical hierarchy process （AHP）, which is an expert system that quantifies the factors of explosion incidents, based on events and hierarchies. In this paper, the proposed model was modification from original AHP model, specifically modifying the structure from ＂alternative＇s results＂ to ＂total risk-rating＇s results＂. The total risk-rating is obtained by summing up risk-rating of each factor, where the risk-rating is a multiplication product of the risk value by the AHP weighted value. To support decision-making using the expert system, data on the real conditions of the CRT were collected and analyzed. A physical modeling of the CRT with laboratory-scale experiments was carried out to show the impact of a ventilation system in CRT on diluting the methane gas and coal dust, in order to support the quantification of AHP risk value. The criteria to evaluate the risk of explosion was constructed from six components that are： fuel, oxygen, ignition, confinement, dispersion, and monitoring system. Those components had fifty-two factors that serve as sub-components （root causes）. The main causes of explosion in CRT were found to be： mechanical ventilation failure and abnormal ventilation, breakdown of monitoring system, and coal spontaneous-combustion. Assessments of two CRT facilities at Mine A and Mine B were carried out as a case study in order to check the reliability of the developed AHP method. The results showed that the risk rating of Mine A was classified as high and Mine B was classified as medium, which is in a good agreement with the site conditions.展开更多
Structural models of credit risk are known to present vanishing spreads at very short maturities. This shortcoming, which is due to the diffusive behavior assumed for asset values, can be circumvented by considering d...Structural models of credit risk are known to present vanishing spreads at very short maturities. This shortcoming, which is due to the diffusive behavior assumed for asset values, can be circumvented by considering discontinuities of the jump type in their evolution over time. In this paper, we extend the pricing model for corporate bond and determine the default probability in jump-diffusion model to address this issue. To make the problem clearly, we first investigate the case that the firm value follows a geometric Brownian motion under similar assumptions to those in Black and Scholes（1973）, Briys and de Varenne（1997）, i.e, the default barrier is KD （t, T） and the recovery rate is （1 -w）, where D （t, T） is the price of zero coupon default free bond and w is a constant （0 〈 w 〈 1）. By changing the numeraire, we obtain the closed-form solution for both the price of bond and default probability. Further, we consider the case of jump-diffusion and suppose that a firm will go bankruptcy if its value Vt 〈 KD （t, T） and at the same time, the bondholder will receive （1 - w） vt/k By introducing the Green function of PDE with absorbing boundary and converting the problem to an II-type Volterra integral equation, we get the closed-form expressions in series form for bond price and corresponding default probability. Numerical results are presented to show the impact of different parameters to credit spread of bond.展开更多
In this paper, we consider a hyper-exponential jump-diffusion model with a constant dividend barrier. Explicit solutions for the Laplace transform of the ruin time, and the Gerber- Shiu function are obtained via marti...In this paper, we consider a hyper-exponential jump-diffusion model with a constant dividend barrier. Explicit solutions for the Laplace transform of the ruin time, and the Gerber- Shiu function are obtained via martingale stopping.展开更多
Refined risk prediction must be achieved to guarantee the safe and steady operation of chemical production processes.However,there is high nonlinearity and association coupling among massive,complicated multisource pr...Refined risk prediction must be achieved to guarantee the safe and steady operation of chemical production processes.However,there is high nonlinearity and association coupling among massive,complicated multisource process data,resulting in a low accuracy of existing prediction technology.For that reason,a real-time risk prediction method for chemical processes based on the attention-based bidirectional long short-term memory(Attention-based Bi-LSTM)is proposed in this study.First,multisource process data,such as temperature,pressure,flow rate,and liquid level,are preprocessed for denoising.Data correlation is analyzed in time windows by setting time windows and moving step lengths to explore correlations,thus establishing a complex network model oriented to the chemical production process.Second,network structure entropy is introduced to reduce the dimensions of the multisource process data.Moreover,a 1D relative risk sequence is acquired by maxemin deviation standardization to judge whether the chemical process is in a steady state.Finally,an Attention-based Bi-LSTM algorithm is established by integrating the attention mechanism and the Bi-LSTM network to fit and train 1D relative risk sequences.In that way,the proposed algorithm achieves real-time prediction and intelligent perception of risk states during chemical production.A case study based on the Tennessee Eastman process(TEP)is conducted.The validity and reasonability of the proposed method are verified by analyzing distribution laws of relative risks under normal and fault conditions.Also,the proposed algorithm importantly improves the prediction accuracy of chemical process risks relative to that of existing prediction technologies.展开更多
In this article, the risk process perturbed by diffusion under interest force is considered, the continuity and twice continuous differentiability for Фδ（u,w） are discussed,the Feller expression and the integro-di...In this article, the risk process perturbed by diffusion under interest force is considered, the continuity and twice continuous differentiability for Фδ（u,w） are discussed,the Feller expression and the integro-differential equation satisfied by Фδ （u ,w） are derived. Finally, the decomposition of Фδ（u,w） is discussed, and some properties of each decomposed part of Фδ（u,w） are obtained. The results can be reduced to some ones in Gerber and Landry＇s,Tsai and Willmot＇s, and Wang＇s works by letting parameter δ and （or） a be zero.展开更多
Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 wo...Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 workflow in such a network. All the sites in the network performed the annual reference dosimetry in water according to TG-51. These data were used to cross-calibrate the same ion chambers in plastic phantoms for monthly QA output measurements. An energy-specific dimensionless beam quality cross-calibration factor, <img src="Edit_6bfb9907-c034-4197-97a7-e8337a7fc21a.png" width="20" height="19" alt="" />, was derived to monitor the process across multiple sites. The SPC analysis was then performed to obtain the mean, <img src="Edit_c630a2dd-f714-4042-a46e-da0ca863cb41.png" width="30" height="20" alt="" /> , standard deviation, <span style="font-size:6.5pt;font-family:;" "=""><span style="white-space:normal;"><span style="font-size:6.5pt;font-family:"">σ</span><span style="white-space:nowrap;"><sub><i>k</i></sub></span></span></span>, the Upper Control Limit (UCL) and Lower Control Limit (LCL) in each beam. This process was first applied to 15 years of historical data at the main campus to assess the effectiveness of the process. A two-year prospective study including all 30 linear accelerators spread over the main campus and seven satellites in the network followed. The ranges of the control limits (±3σ) were found to be in the range of 1.7% - 2.6% and 3.3% - 4.2% for the main campus and the satellite sites respectively. The wider range in the satellite sites was attributed to variations in the workflow. Standardization of workflow was also found to be effective in narrowing the control limits. The SPC is effective in identifying variations in the workflow and was shown to be an effective tool in managing large network reference dosimetry.展开更多
Sale-leaseback is paid special focus on for its great application in China in recent years.By giving a detailed analysis,an analysis of the features of sale-leaseback and a study of the risks of it are given in this p...Sale-leaseback is paid special focus on for its great application in China in recent years.By giving a detailed analysis,an analysis of the features of sale-leaseback and a study of the risks of it are given in this paper.Then a quantitative analysis of commercial real estate sale-leaseback is carried out.The scientific theoretical analysis is provided in this paper for risk assessment in commercial real estate sale-leaseback mode in China.An effective approach is put forward for sale-leaseback project evaluation and prevention of risk.A useful means is given to supervise commerciai real estate sale-leaseback mode for relevant departments and a certain contribution is made to a further sound development of commercial real estate sale-leaseback mode.展开更多
基金Supported by the National Natural Sci-ence Foundations of China (10271062 and 10471119)the Natural Science Foundation of Shandong Province(Y2004A06, Y2008A12, and ZR2009AL015)+1 种基金the Science Foundations of Shandong Provincial Education Department (J07yh05)the Science Foundations of Qufu Normal University (XJ0713, Bsqd200517)
文摘In this article, the joint distributions of several actuarial diagnostics which are important to insurers＇ running for the jump-diffusion risk process are examined. They include the ruin time, the time of the surplus process leaving zero ultimately （simply, the ultimately leaving-time）, the surplus immediately prior to ruin, the supreme profits before ruin, the supreme profits and deficit until it leaves zero ultimately and so on. The explicit expressions for their distributions are obtained mainly by the various properties of Levy process, such as the homogeneous strong Markov property and the spatial homogeneity property etc, moveover, the many properties for Brownian motion.
文摘The classical Poisson risk model in ruin theory assumed that the interarrival times between two successive claims are mutually independent, and the claim sizes and claim intervals are also mutually independent. In this paper, we modify the classical Poisson risk model to describe the surplus process of an insurance portfolio. We consider a jump-diffusion risk process compounded by a geometric Brownian motion, and assume that the claim sizes and claim intervals are dependent. Using the properties of conditional expectation, we establish integro-differential equations for the Gerber-Shiu function and the ultimate ruin probability.
基金Supported by the Humanity and Social Science Foundation of Ministry of Education of China(10YJC790296)Supported by the National Natural Science Foundation of China(71073020)
文摘In this paper, the optimal XL-reinsurance of an insurer with jump-diffusion risk process is studied. With the assumptions that the risk process is a compound Possion process perturbed by a standard Brownian motion and the reinsurance premium is calculated according to the variance principle, the implicit expression of the priority and corresponding value function when the utility function is exponential are obtained. At last, the value function is argued, the properties of the priority about parameters are discussed and numerical results of the priority for various claim-size distributions are shown.
基金Supported by the NNSF of China(40675023)the PHD Foundation of Guangxi Normal University.
文摘Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.
文摘A framework for the optimal sparse-control of the probability density function of a jump-diffusion process is presented. This framework is based on the partial integro-differential Fokker-Planck (FP) equation that governs the time evolution of the probability density function of this process. In the stochastic process and, correspondingly, in the FP model the control function enters as a time-dependent coefficient. The objectives of the control are to minimize a discrete-in-time, resp. continuous-in-time, tracking functionals and its L2- and L1-costs, where the latter is considered to promote control sparsity. An efficient proximal scheme for solving these optimal control problems is considered. Results of numerical experiments are presented to validate the theoretical results and the computational effectiveness of the proposed control framework.
基金supported by the project VSB-TU Ostrava,SP2024/045.
文摘Renewable energy sources,including wind,solar,and biofuels,are essential for promoting sustainable economic development and mitigating environmental challenges.As China’s overseas investments in renewable energy expand,effective risk assessment and management have become critical.This study develops a comprehensive risk evaluation framework for China’s overseas renewable energy investments using the Fuzzy Analytic Hierarchy Process(FAHP).The framework incorporates political,economic,and project-specific risks,organized through three primary criteria,nine sub-criteria,and thirty tertiary indicators.By integrating expert judgments with fuzzy set theory,the FAHP methodology assigns accurate weights to risk factors and ensures consistency in evaluation.The findings identify political risks as the most significant,emphasizing their influence on investment strategies.These insights offer valuable guidance for policymakers and investors to enhance risk management strategies and ensure the sustainability of China’s renewable energy initiatives abroad.
文摘In this paper,a class of risk processes perturbed by diffusion are considered. The Lundberg inequalities for the ruin probability are obtained.The size of the Lundberg exponents for different kinds of risk model is compared. The numerical illustration for the impact of the parameters on the ruin probability is given.
基金supported by a grant from the National Ministry of Science and Technology(No.2013ZX09402203)
文摘Analysis errors can occur in the desorbing process of ginkgo diterpene lactone meglumine injection(GDMI) by a conventional analysis method, due to several factors, such as easily crystallized samples, solvent volatility, time-consuming sample pre-processing, fixed method, and offline analysis. Based on risk management, near-infrared(NIR) and mid-infrared(MIR) spectroscopy techniques were introduced to solve the above problems with the advantage of timely analysis and non-destructive nature towards samples. The objective of the present study was to identify the feasibility of using NIR or MIR spectroscopy techniques to increase the analysis accuracy of samples from the desorbing process of GDMI. Quantitative models of NIR and MIR were established based on partial least square method and the performances were calculated. Compared to NIR model, MIR model showed greater accuracy and applicability for the analysis of the GDMI desorbing solutions. The relative errors of the concentrations of Ginkgolide A(GA) and Ginkgolide B(GB) were 2.40% and 2.89%, respectively, which were less than 5.00%. The research demonstrated the potential of the MIR spectroscopy technique for the rapid and non-destructive quantitative analysis of the concentrations of GA and GB.
基金financially supported by the National Key Research and Development Program of China (2016YFB1200401)the Western Construction Project of the Ministry of Transport (Grant No. 2015318J29040)
文摘Seismic risk evaluation(SRE) in early stages(e.g., project planning and preliminary design)for a mountain tunnel located in seismic areas has the same importance as that in final stages(e.g.,performance-based design, structural analysis, and optimization). SRE for planning mountain tunnels bridges the gap between the planning on the macro level and the design/analysis on the micro level regarding the risk management of infrastructural systems. A transition from subjective or qualitative description to objective or quantitative quantification of seismic risk is aimed to improve the seismic behavior of the mountain tunnel and thus reduce the associated seismic risk. A new method of systematic SRE for the planning mountain tunnel was presented herein. The method employs extension theory(ET)and an ET-based improved analytical hierarchy process. Additionally, a new risk-classification criterion is proposed to classify and quantify the seismic risk for a planning mountain tunnel. This SRE method is applied to a mountain tunnel in southwest China, using the extension model based on matter element theory and dependent function operation.The reasonability and flexibility of the SRE method for application to the mountain tunnel are illustrated.According to different seismic risk levels and classification criteria, methods and measures for improving the seismic design are proposed, which can reduce the seismic risk and provide a frame of reference for elaborate seismic design.
基金Project(50977003) supported by the National Natural Science Foundation of China
文摘In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.
文摘Markov decision processes （MDPs） and their variants are widely studied in the theory of controls for stochastic discrete- event systems driven by Markov chains. Much of the literature focusses on the risk-neutral criterion in which the expected rewards, either average or discounted, are maximized. There exists some literature on MDPs that takes risks into account. Much of this addresses the exponential utility （EU） function and mechanisms to penalize different forms of variance of the rewards. EU functions have some numerical deficiencies, while variance measures variability both above and below the mean rewards; the variability above mean rewards is usually beneficial and should not be penalized/avoided. As such, risk metrics that account for pre-specified targets （thresholds） for rewards have been considered in the literature, where the goal is to penalize the risks of revenues falling below those targets. Existing work on MDPs that takes targets into account seeks to minimize risks of this nature. Minimizing risks can lead to poor solutions where the risk is zero or near zero, but the average rewards are also rather low. In this paper, hence, we study a risk-averse criterion, in particular the so-called downside risk, which equals the probability of the revenues falling below a given target, where, in contrast to minimizing such risks, we only reduce this risk at the cost of slightly lowered average rewards. A solution where the risk is low and the average reward is quite high, although not at its maximum attainable value, is very attractive in practice. To be more specific, in our formulation, the objective function is the expected value of the rewards minus a scalar times the downside risk. In this setting, we analyze the infinite horizon MDP, the finite horizon MDP, and the infinite horizon semi-MDP （SMDP）. We develop dynamic programming and reinforcement learning algorithms for the finite and infinite horizon. The algorithms are tested in numerical studies and show encouraging performance.
文摘Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually since it won a contract for a nuclear power plant construction project in the United Arab Emirates in 2009. However, time and monetary resources have been lost in some nuclear power plant construction sites due to lack of risk management ability. The need to prevent losses at nuclear power plant construction sites has become more urgent because it demands professional skills and large-scale resources. Therefore, in this study, the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) were applied in order to make comparisons between decision-making methods, to assess the potential risks at nuclear power plant construction sites. To suggest the appropriate choice between two decision-making methods, a survey was carried out. From the results, the importance and the priority of 24 risk factors, classified by process, cost, safety, and quality, were analyzed. The FAHP was identified as a suitable method for risk assessment of nuclear power plant construction, compared with risk assessment using the AHP. These risk factors will be able to serve as baseline data for risk management in nuclear power plant construction projects.
基金Supported by the Foundation of Suzhou Science and Technology University
文摘This paper studies a Sparre Andersen negative risk sums model in which the distribution of ＂interclaim＂ time is that of a sum of n independent exponential random variables. Thus, the Erlang（n） model is a special case. On this basis the correlated negative risk sums process with the common Erlang process is considered. Integro-differential equations with boundary conditions for ψ（u） are given. For some special cases a closed-form expression for ψ（u） is derived.
文摘This study focused on developing a risk assessment method for explosion at a coal reclaim tunnel （CRT） facility. The method was developed based on an analytical hierarchy process （AHP）, which is an expert system that quantifies the factors of explosion incidents, based on events and hierarchies. In this paper, the proposed model was modification from original AHP model, specifically modifying the structure from ＂alternative＇s results＂ to ＂total risk-rating＇s results＂. The total risk-rating is obtained by summing up risk-rating of each factor, where the risk-rating is a multiplication product of the risk value by the AHP weighted value. To support decision-making using the expert system, data on the real conditions of the CRT were collected and analyzed. A physical modeling of the CRT with laboratory-scale experiments was carried out to show the impact of a ventilation system in CRT on diluting the methane gas and coal dust, in order to support the quantification of AHP risk value. The criteria to evaluate the risk of explosion was constructed from six components that are： fuel, oxygen, ignition, confinement, dispersion, and monitoring system. Those components had fifty-two factors that serve as sub-components （root causes）. The main causes of explosion in CRT were found to be： mechanical ventilation failure and abnormal ventilation, breakdown of monitoring system, and coal spontaneous-combustion. Assessments of two CRT facilities at Mine A and Mine B were carried out as a case study in order to check the reliability of the developed AHP method. The results showed that the risk rating of Mine A was classified as high and Mine B was classified as medium, which is in a good agreement with the site conditions.
基金Supported by the National Basic Research Program of China(973 Program)(2007CB814903)
文摘Structural models of credit risk are known to present vanishing spreads at very short maturities. This shortcoming, which is due to the diffusive behavior assumed for asset values, can be circumvented by considering discontinuities of the jump type in their evolution over time. In this paper, we extend the pricing model for corporate bond and determine the default probability in jump-diffusion model to address this issue. To make the problem clearly, we first investigate the case that the firm value follows a geometric Brownian motion under similar assumptions to those in Black and Scholes（1973）, Briys and de Varenne（1997）, i.e, the default barrier is KD （t, T） and the recovery rate is （1 -w）, where D （t, T） is the price of zero coupon default free bond and w is a constant （0 〈 w 〈 1）. By changing the numeraire, we obtain the closed-form solution for both the price of bond and default probability. Further, we consider the case of jump-diffusion and suppose that a firm will go bankruptcy if its value Vt 〈 KD （t, T） and at the same time, the bondholder will receive （1 - w） vt/k By introducing the Green function of PDE with absorbing boundary and converting the problem to an II-type Volterra integral equation, we get the closed-form expressions in series form for bond price and corresponding default probability. Numerical results are presented to show the impact of different parameters to credit spread of bond.
基金Supported by the Natural Science Foundation of Jiangsu Province(BK20130260)the National Natural Science Foundation of China(11301369)the Postdoctoral Science Foundation of China(2013M540371)
文摘In this paper, we consider a hyper-exponential jump-diffusion model with a constant dividend barrier. Explicit solutions for the Laplace transform of the ruin time, and the Gerber- Shiu function are obtained via martingale stopping.
基金supported by the National Natural Science Foundation of China(52004014)the Fundamental Research Funds for the Central Universities(ZY2406)the National Key Research&Development Program of China(2021YFB3301100).
文摘Refined risk prediction must be achieved to guarantee the safe and steady operation of chemical production processes.However,there is high nonlinearity and association coupling among massive,complicated multisource process data,resulting in a low accuracy of existing prediction technology.For that reason,a real-time risk prediction method for chemical processes based on the attention-based bidirectional long short-term memory(Attention-based Bi-LSTM)is proposed in this study.First,multisource process data,such as temperature,pressure,flow rate,and liquid level,are preprocessed for denoising.Data correlation is analyzed in time windows by setting time windows and moving step lengths to explore correlations,thus establishing a complex network model oriented to the chemical production process.Second,network structure entropy is introduced to reduce the dimensions of the multisource process data.Moreover,a 1D relative risk sequence is acquired by maxemin deviation standardization to judge whether the chemical process is in a steady state.Finally,an Attention-based Bi-LSTM algorithm is established by integrating the attention mechanism and the Bi-LSTM network to fit and train 1D relative risk sequences.In that way,the proposed algorithm achieves real-time prediction and intelligent perception of risk states during chemical production.A case study based on the Tennessee Eastman process(TEP)is conducted.The validity and reasonability of the proposed method are verified by analyzing distribution laws of relative risks under normal and fault conditions.Also,the proposed algorithm importantly improves the prediction accuracy of chemical process risks relative to that of existing prediction technologies.
文摘In this article, the risk process perturbed by diffusion under interest force is considered, the continuity and twice continuous differentiability for Фδ（u,w） are discussed,the Feller expression and the integro-differential equation satisfied by Фδ （u ,w） are derived. Finally, the decomposition of Фδ（u,w） is discussed, and some properties of each decomposed part of Фδ（u,w） are obtained. The results can be reduced to some ones in Gerber and Landry＇s,Tsai and Willmot＇s, and Wang＇s works by letting parameter δ and （or） a be zero.
文摘Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 workflow in such a network. All the sites in the network performed the annual reference dosimetry in water according to TG-51. These data were used to cross-calibrate the same ion chambers in plastic phantoms for monthly QA output measurements. An energy-specific dimensionless beam quality cross-calibration factor, <img src="Edit_6bfb9907-c034-4197-97a7-e8337a7fc21a.png" width="20" height="19" alt="" />, was derived to monitor the process across multiple sites. The SPC analysis was then performed to obtain the mean, <img src="Edit_c630a2dd-f714-4042-a46e-da0ca863cb41.png" width="30" height="20" alt="" /> , standard deviation, <span style="font-size:6.5pt;font-family:;" "=""><span style="white-space:normal;"><span style="font-size:6.5pt;font-family:"">σ</span><span style="white-space:nowrap;"><sub><i>k</i></sub></span></span></span>, the Upper Control Limit (UCL) and Lower Control Limit (LCL) in each beam. This process was first applied to 15 years of historical data at the main campus to assess the effectiveness of the process. A two-year prospective study including all 30 linear accelerators spread over the main campus and seven satellites in the network followed. The ranges of the control limits (±3σ) were found to be in the range of 1.7% - 2.6% and 3.3% - 4.2% for the main campus and the satellite sites respectively. The wider range in the satellite sites was attributed to variations in the workflow. Standardization of workflow was also found to be effective in narrowing the control limits. The SPC is effective in identifying variations in the workflow and was shown to be an effective tool in managing large network reference dosimetry.
文摘Sale-leaseback is paid special focus on for its great application in China in recent years.By giving a detailed analysis,an analysis of the features of sale-leaseback and a study of the risks of it are given in this paper.Then a quantitative analysis of commercial real estate sale-leaseback is carried out.The scientific theoretical analysis is provided in this paper for risk assessment in commercial real estate sale-leaseback mode in China.An effective approach is put forward for sale-leaseback project evaluation and prevention of risk.A useful means is given to supervise commerciai real estate sale-leaseback mode for relevant departments and a certain contribution is made to a further sound development of commercial real estate sale-leaseback mode.
