To mitigate the damages produced by flood discharges of hydropower stations, a three-dimensional numerical model of the aerated water jet restricted by gravity, air resistance and air buoyancy is proposed. Based on th...To mitigate the damages produced by flood discharges of hydropower stations, a three-dimensional numerical model of the aerated water jet restricted by gravity, air resistance and air buoyancy is proposed. Based on theoretical analysis and prototype data, a three-dimensional stochastic model is constructed using Monte Carlo method to evaluate the range of atomization and intensity of rainfall in gorges, which are strongly affected by complex terrain and various wind conditions. The prototype data observed from two hydropower stations are selected in the feedback and verification analysis to verify the proposed model. The result shows that the computational solutions fit the prototype data well. This model can be used to forecast the atomization of a hydropower station that is being designed or constructed.展开更多
Monte Carlo simulation was applied to Assembly Success Bate (ASK) analyses. ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes, manufacturing tolerances and robot repea...Monte Carlo simulation was applied to Assembly Success Bate (ASK) analyses. ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes, manufacturing tolerances and robot repeatability into account. A statistic arithmetic expression was proposed and deduced in this paper, which offers an alternative method of estimating the accuracy of ASR, without having to repeat the simulations. This statistic method also helps to choose a suitable sample size, if error reduction is desired. Monte Carlo simulation results demonstrated the feasibility of the method.展开更多
Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algor...Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algorithm is compared with Monte Carlo simulated annealing algorithm, and its feasibility and effectiveness are verified with two calculating examples.展开更多
Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) sl...Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) slopes is studied in this paper. The slope safety factor is computed by combining the kinematic approach of limit analysis using a three-dimensional rotational failure mechanism with the pseudo-dynamic approach. The variability of input parameters, including six pseudo-dynamic parameters and two soil shear strength parameters, are taken into account by means of Monte-Carlo Simulations (MCS) method. The influences of pseudo-dynamic input variables on the computed failure probabilities are investigated and discussed. It is shown that the obtained failure probabilities increase with the pseudo-dynamic input variables and the pseudo-dynamic approach gives more conservative failure probability estimates compared with the pseudo-static approach.展开更多
In this paper,application of Sequential Quasi Monte Carlo(SQMC)to blind channel andsymbol joint estimation in cooperative Multiple-Input Multiple-Output(MIMO)system is proposed,which does not need to transmit training...In this paper,application of Sequential Quasi Monte Carlo(SQMC)to blind channel andsymbol joint estimation in cooperative Multiple-Input Multiple-Output(MIMO)system is proposed,which does not need to transmit training symbol and can save the power and channel bandwidth.Additionally,an improved version of SQMC algorithm by taking advantage of current received signal isdiscussed.Simulation results show that the SQMC method outperforms the Sequential Monte Carlo(SMC)methods,and the incorporation of current received signal improves the performance of theSQMC obviously.展开更多
In this paper, we revisit foundations of the applications of physical measurement and Lindenmayer system to the modeling of plants. The measurement is proposed to a formal procedure and measuring the mass of leaves on...In this paper, we revisit foundations of the applications of physical measurement and Lindenmayer system to the modeling of plants. The measurement is proposed to a formal procedure and measuring the mass of leaves on a tree, tailored to branching plant structures with Simpson＇ s rule and Monte Carlo Methods. L-system is possible to visualize mathematical models of biological structures and processes. The formalism is illustrated using theoretical branching systems, and applied to analyze total leaves number as well as total weight of them.展开更多
In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library, a new Genetic Algorithm (GA)-based techni...In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library, a new Genetic Algorithm (GA)-based technique is developed to determine the maximum power dissipation from a statistical point of view. The simulation on 1SCAS-89 benchmarks shows that the ratio of the maximum power dissipation with glitching activity over the maximum power under zero-delay model ranges from 1.18 to 4.02. Compared with the traditional Monte Carlo-based technique, the new approach presented in this paper is more effective.展开更多
Pricing variance swaps under stochastic volatility has been an important subject pursued recently. Various approaches have been proposed, mainly due to the substantially increased trading activities of volatility-rela...Pricing variance swaps under stochastic volatility has been an important subject pursued recently. Various approaches have been proposed, mainly due to the substantially increased trading activities of volatility-related derivatives in the past few years. In this note, the authors develop analytical method for pricing variance swaps under stochastic volatility with an Ornstein-Uhlenbeck(OU) process. By using Fourier transform algorithm, a closed-form solution for pricing variance swaps with stochastic volatility is obtained, and to give a comparison of fair strike value based on the discrete model, continuous model, and the Monte Carlo simulations.展开更多
A methodology for kinetic modeling of conversion processes is presented.The proposed approach allows to overcome the lack of molecular detail of the petroleum fractions and to simulate the reactions of the process by ...A methodology for kinetic modeling of conversion processes is presented.The proposed approach allows to overcome the lack of molecular detail of the petroleum fractions and to simulate the reactions of the process by means of a two-step procedure.In the first step,a synthetic mixture of molecules representing the feedstock is generated via a molecular reconstruction method,termed SR-REM molecular reconstruction.In the second step,a kinetic Monte Carlo method,termed stochastic simulation algorithm(SSA),is used to simulate the effect of the conversion reactions on the mixture of molecules.The resulting methodology is applied to the Athabasca vacuum residue hydrocracking.An adequate molecular representation of the vacuum residue is obtained using the SR-REM algorithm.The reaction simulations present a good agreement with the laboratory data for Athabasca vacuum residue conversion.In addition,the proposed methodology provides the molecular detail of the vacuum residue conversion throughout the reactions simulations.展开更多
We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH mo...We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator.The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions.The proposed methodology is also illustrated by Va R on stock price data.展开更多
The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likeli...The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likelihood estimate for the regression coefficient in the Cox model.This method was shown not as sensitive to heavy censoring as the bootstrap method in simulation studies but it may not be second-order accurate as was shown for the bootstrap approximation.In this paper,we propose an alternative random weighting method based on one-step linear jackknife pseudo values and prove the second accuracy of the proposed method.Monte Carlo simulations are also performed to evaluate the proposed method for fixed sample sizes.展开更多
基金Supported by Natural Science Foundation of China (No.50379033)Program for New Century Excellent Talents in University.
文摘To mitigate the damages produced by flood discharges of hydropower stations, a three-dimensional numerical model of the aerated water jet restricted by gravity, air resistance and air buoyancy is proposed. Based on theoretical analysis and prototype data, a three-dimensional stochastic model is constructed using Monte Carlo method to evaluate the range of atomization and intensity of rainfall in gorges, which are strongly affected by complex terrain and various wind conditions. The prototype data observed from two hydropower stations are selected in the feedback and verification analysis to verify the proposed model. The result shows that the computational solutions fit the prototype data well. This model can be used to forecast the atomization of a hydropower station that is being designed or constructed.
文摘Monte Carlo simulation was applied to Assembly Success Bate (ASK) analyses. ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes, manufacturing tolerances and robot repeatability into account. A statistic arithmetic expression was proposed and deduced in this paper, which offers an alternative method of estimating the accuracy of ASR, without having to repeat the simulations. This statistic method also helps to choose a suitable sample size, if error reduction is desired. Monte Carlo simulation results demonstrated the feasibility of the method.
文摘Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algorithm is compared with Monte Carlo simulated annealing algorithm, and its feasibility and effectiveness are verified with two calculating examples.
文摘Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) slopes is studied in this paper. The slope safety factor is computed by combining the kinematic approach of limit analysis using a three-dimensional rotational failure mechanism with the pseudo-dynamic approach. The variability of input parameters, including six pseudo-dynamic parameters and two soil shear strength parameters, are taken into account by means of Monte-Carlo Simulations (MCS) method. The influences of pseudo-dynamic input variables on the computed failure probabilities are investigated and discussed. It is shown that the obtained failure probabilities increase with the pseudo-dynamic input variables and the pseudo-dynamic approach gives more conservative failure probability estimates compared with the pseudo-static approach.
基金the National Natural Science Foundation of China(No.60372107)the Ph.D.Innovation Programof Jiangsu Province(No.200670).
文摘In this paper,application of Sequential Quasi Monte Carlo(SQMC)to blind channel andsymbol joint estimation in cooperative Multiple-Input Multiple-Output(MIMO)system is proposed,which does not need to transmit training symbol and can save the power and channel bandwidth.Additionally,an improved version of SQMC algorithm by taking advantage of current received signal isdiscussed.Simulation results show that the SQMC method outperforms the Sequential Monte Carlo(SMC)methods,and the incorporation of current received signal improves the performance of theSQMC obviously.
文摘In this paper, we revisit foundations of the applications of physical measurement and Lindenmayer system to the modeling of plants. The measurement is proposed to a formal procedure and measuring the mass of leaves on a tree, tailored to branching plant structures with Simpson＇ s rule and Monte Carlo Methods. L-system is possible to visualize mathematical models of biological structures and processes. The formalism is illustrated using theoretical branching systems, and applied to analyze total leaves number as well as total weight of them.
基金Supported by NSF of the United States under contract 5978 East Asia and Pacific Program 9602485
文摘In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library, a new Genetic Algorithm (GA)-based technique is developed to determine the maximum power dissipation from a statistical point of view. The simulation on 1SCAS-89 benchmarks shows that the ratio of the maximum power dissipation with glitching activity over the maximum power under zero-delay model ranges from 1.18 to 4.02. Compared with the traditional Monte Carlo-based technique, the new approach presented in this paper is more effective.
基金supported by the National Social Science Fund of China under Grant No.14ATJ005Anhui Provincial Natural Science Foundation under Grant Nos.1308085MF93 and 1408085MKL84the National Natural Science Foundations of China under Grant No.11401556
文摘Pricing variance swaps under stochastic volatility has been an important subject pursued recently. Various approaches have been proposed, mainly due to the substantially increased trading activities of volatility-related derivatives in the past few years. In this note, the authors develop analytical method for pricing variance swaps under stochastic volatility with an Ornstein-Uhlenbeck(OU) process. By using Fourier transform algorithm, a closed-form solution for pricing variance swaps with stochastic volatility is obtained, and to give a comparison of fair strike value based on the discrete model, continuous model, and the Monte Carlo simulations.
文摘A methodology for kinetic modeling of conversion processes is presented.The proposed approach allows to overcome the lack of molecular detail of the petroleum fractions and to simulate the reactions of the process by means of a two-step procedure.In the first step,a synthetic mixture of molecules representing the feedstock is generated via a molecular reconstruction method,termed SR-REM molecular reconstruction.In the second step,a kinetic Monte Carlo method,termed stochastic simulation algorithm(SSA),is used to simulate the effect of the conversion reactions on the mixture of molecules.The resulting methodology is applied to the Athabasca vacuum residue hydrocracking.An adequate molecular representation of the vacuum residue is obtained using the SR-REM algorithm.The reaction simulations present a good agreement with the laboratory data for Athabasca vacuum residue conversion.In addition,the proposed methodology provides the molecular detail of the vacuum residue conversion throughout the reactions simulations.
基金supported by National Natural Science Foundation of China(Grant No.11371354)Key Laboratory of Random Complex Structures and Data Science+2 种基金Chinese Academy of Sciences(Grant No.2008DP173182)National Center for Mathematics and Interdisciplinary SciencesChinese Academy of Sciences
文摘We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator.The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions.The proposed methodology is also illustrated by Va R on stock price data.
基金supported by Natural Science and Engineering Research Council of Canada and National Natural Science Foundation of China (Grant No. 10871188)
文摘The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likelihood estimate for the regression coefficient in the Cox model.This method was shown not as sensitive to heavy censoring as the bootstrap method in simulation studies but it may not be second-order accurate as was shown for the bootstrap approximation.In this paper,we propose an alternative random weighting method based on one-step linear jackknife pseudo values and prove the second accuracy of the proposed method.Monte Carlo simulations are also performed to evaluate the proposed method for fixed sample sizes.
