在定义计划评审技术(program evaluation and review technique,PERT)网络局部关键活动、关键活动、关键路线和活动关键度的基础上,提出了关键活动、关键路线的分析方法;根据活动不确定性对项目计划工期影响的大小,即活动敏感性指标的大...在定义计划评审技术(program evaluation and review technique,PERT)网络局部关键活动、关键活动、关键路线和活动关键度的基础上,提出了关键活动、关键路线的分析方法;根据活动不确定性对项目计划工期影响的大小,即活动敏感性指标的大小,确定活动在项目进度控制中的重要程度;在定义活动相对敏感性、活动敏感性的基础上,利用全概率公式,得到活动敏感性指标计算公式,进而提出了最关键活动分析方法。算例表明,利用本研究提出的方法可便捷地找出PERT网络的关键路线和最关键活动。展开更多
Monte Carlo(Mc)模拟被广泛应用于光子在生物组织中的传输研究。通常模拟时将生物组织近似为均匀的平板分层介质,当层状生物组织中含有异常物质(如肿瘤细胞等)或正常生物组织为非平板的复杂结构时,其模拟中的组织模型将会有相应的改变...Monte Carlo(Mc)模拟被广泛应用于光子在生物组织中的传输研究。通常模拟时将生物组织近似为均匀的平板分层介质,当层状生物组织中含有异常物质(如肿瘤细胞等)或正常生物组织为非平板的复杂结构时,其模拟中的组织模型将会有相应的改变。通过探讨这几类生物组织的MC模拟模型,总结并分析模型建立的关键问题,对基于MC模拟的各种生物组织光学检测研究提供了指导。展开更多
A method which adopts the combination of least squares support vector machine（LS-SVM） and Monte Carlo（MC） simulation is used to calculate the foundation settlement reliability.When using LS-SVM,choosing the traini...A method which adopts the combination of least squares support vector machine（LS-SVM） and Monte Carlo（MC） simulation is used to calculate the foundation settlement reliability.When using LS-SVM,choosing the training dataset and the values for LS-SVM parameters is the key.In a representative sense,the orthogonal experimental design with four factors and five levels is used to choose the inputs of the training dataset,and the outputs are calculated by using fast Lagrangian analysis continua（FLAC）.The decimal ant colony algorithm（DACA） is also used to determine the parameters.Calculation results show that the values of the two parameters,and δ2 have great effect on the performance of LS-SVM.After the training of LS-SVM,the inputs are sampled according to the probabilistic distribution,and the outputs are predicted with the trained LS-SVM,thus the reliability analysis can be performed by the MC method.A program compiled by Matlab is employed to calculate its reliability.Results show that the method of combining LS-SVM and MC simulation is applicable to the reliability analysis of soft foundation settlement.展开更多
We present a Monte Carlo (MC) method to simulate the scattering for medium within randomly distributed particles, discuss the convergence of this method by varying the size parameter ka, volume parameter η and calcul...We present a Monte Carlo (MC) method to simulate the scattering for medium within randomly distributed particles, discuss the convergence of this method by varying the size parameter ka, volume parameter η and calculation parameter Ni, then compare this method with the classical iteration method with the same parameters. The calculation results showed that this method has good convergence and accords with the iteration method while consuming less CPU time. At the end of this paper, this method is used to discuss the visual light scatter in the c-Si/α-Si films.展开更多
The income approach of asset valuation estimates the asset value according to the asset-discounted future earnings or the capitalizing process. As a result, a reasonable prediction of asset-expected future returns has...The income approach of asset valuation estimates the asset value according to the asset-discounted future earnings or the capitalizing process. As a result, a reasonable prediction of asset-expected future returns has become one of the core contents of the income approach. The forecast on expected future earnings is generally based on many uncertain factors, such as strict conditions of assumption and the complexity of environment. However, the current valuation practice in this aspect varies greatly and sometimes depends on personally experienced judgment of appraisers. Therefore, the obtained valuation results tend to be simplified and absolutized. This paper takes a listed company in China as an example to explore the way of inserting an uncertainty analysis into the prediction of the income approach, and then to obtain a series of valuation results within a certain probability fluctuation range. Finally, it puts forward some suggestions about the Monte Carlo simulation （MCS）.展开更多
As one of the major methods for the simulation of option pricing,Monte Carlo method assumes random fluctuations in the distribution of asset prices.Under certain uncertainties process,different evolution paths could b...As one of the major methods for the simulation of option pricing,Monte Carlo method assumes random fluctuations in the distribution of asset prices.Under certain uncertainties process,different evolution paths could be simulated so as to finally yield the expectation value of the asset price,which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations.In order to solve the above computational problem,quantum Monte Carlo(QMC)has been established and applied in the relevant systems such as European call options.In this work,both MC and QM methods are adopted to simulate European call options.Based on the preparation of quantum states in QMC algorithm and the construction of quantum circuits by simulating a quantum hardware environment on a traditional computer,the amplitude estimation(AE)algorithm is found to play a secondary role in accelerating the pricing of European options.More importantly,the payoff function and the time required for the simulation in QMC method show some improvements than those in MC method.展开更多
应力强度因子是预测荷载作用下结构中裂纹产生和扩展的重要参数。半解析的比例边界有限元法结合了有限元和边界元法的优势,在裂纹尖端或存在奇异应力的区域不需要局部网格细化,可以直接提取应力强度因子。在比例边界有限元法计算应力强...应力强度因子是预测荷载作用下结构中裂纹产生和扩展的重要参数。半解析的比例边界有限元法结合了有限元和边界元法的优势,在裂纹尖端或存在奇异应力的区域不需要局部网格细化,可以直接提取应力强度因子。在比例边界有限元法计算应力强度因子的框架下,引入随机参数进行蒙特卡罗模拟(Monte Carlo simulation, MCS),并提出一种新颖的基于MCS的不确定量化分析。与直接的MCS不同,采用奇异值分解构造低阶的子空间,降低系统的自由度,并使用径向基函数对子空间进行近似,通过子空间的线性组合获得新的结构响应,实现基于MCS的快速不确定量化分析。考虑不同荷载状况下,结构形状参数和材料属性参数对应力强度因子的影响,使用改进的MCS计算应力强度因子的统计特征,量化不确定参数对结构的影响。最后通过若干算例验证了该算法的准确性和有效性。展开更多
文摘在定义计划评审技术(program evaluation and review technique,PERT)网络局部关键活动、关键活动、关键路线和活动关键度的基础上,提出了关键活动、关键路线的分析方法;根据活动不确定性对项目计划工期影响的大小,即活动敏感性指标的大小,确定活动在项目进度控制中的重要程度;在定义活动相对敏感性、活动敏感性的基础上,利用全概率公式,得到活动敏感性指标计算公式,进而提出了最关键活动分析方法。算例表明,利用本研究提出的方法可便捷地找出PERT网络的关键路线和最关键活动。
文摘A method which adopts the combination of least squares support vector machine（LS-SVM） and Monte Carlo（MC） simulation is used to calculate the foundation settlement reliability.When using LS-SVM,choosing the training dataset and the values for LS-SVM parameters is the key.In a representative sense,the orthogonal experimental design with four factors and five levels is used to choose the inputs of the training dataset,and the outputs are calculated by using fast Lagrangian analysis continua（FLAC）.The decimal ant colony algorithm（DACA） is also used to determine the parameters.Calculation results show that the values of the two parameters,and δ2 have great effect on the performance of LS-SVM.After the training of LS-SVM,the inputs are sampled according to the probabilistic distribution,and the outputs are predicted with the trained LS-SVM,thus the reliability analysis can be performed by the MC method.A program compiled by Matlab is employed to calculate its reliability.Results show that the method of combining LS-SVM and MC simulation is applicable to the reliability analysis of soft foundation settlement.
基金Project (No. 2004AA32G040) supported by the Hi-Tech Researchand Development Program (863) of China
文摘We present a Monte Carlo (MC) method to simulate the scattering for medium within randomly distributed particles, discuss the convergence of this method by varying the size parameter ka, volume parameter η and calculation parameter Ni, then compare this method with the classical iteration method with the same parameters. The calculation results showed that this method has good convergence and accords with the iteration method while consuming less CPU time. At the end of this paper, this method is used to discuss the visual light scatter in the c-Si/α-Si films.
文摘The income approach of asset valuation estimates the asset value according to the asset-discounted future earnings or the capitalizing process. As a result, a reasonable prediction of asset-expected future returns has become one of the core contents of the income approach. The forecast on expected future earnings is generally based on many uncertain factors, such as strict conditions of assumption and the complexity of environment. However, the current valuation practice in this aspect varies greatly and sometimes depends on personally experienced judgment of appraisers. Therefore, the obtained valuation results tend to be simplified and absolutized. This paper takes a listed company in China as an example to explore the way of inserting an uncertainty analysis into the prediction of the income approach, and then to obtain a series of valuation results within a certain probability fluctuation range. Finally, it puts forward some suggestions about the Monte Carlo simulation （MCS）.
基金This work was financially supported by the National Natural Science Foundation of China Granted No.11764028。
文摘As one of the major methods for the simulation of option pricing,Monte Carlo method assumes random fluctuations in the distribution of asset prices.Under certain uncertainties process,different evolution paths could be simulated so as to finally yield the expectation value of the asset price,which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations.In order to solve the above computational problem,quantum Monte Carlo(QMC)has been established and applied in the relevant systems such as European call options.In this work,both MC and QM methods are adopted to simulate European call options.Based on the preparation of quantum states in QMC algorithm and the construction of quantum circuits by simulating a quantum hardware environment on a traditional computer,the amplitude estimation(AE)algorithm is found to play a secondary role in accelerating the pricing of European options.More importantly,the payoff function and the time required for the simulation in QMC method show some improvements than those in MC method.
文摘应力强度因子是预测荷载作用下结构中裂纹产生和扩展的重要参数。半解析的比例边界有限元法结合了有限元和边界元法的优势,在裂纹尖端或存在奇异应力的区域不需要局部网格细化,可以直接提取应力强度因子。在比例边界有限元法计算应力强度因子的框架下,引入随机参数进行蒙特卡罗模拟(Monte Carlo simulation, MCS),并提出一种新颖的基于MCS的不确定量化分析。与直接的MCS不同,采用奇异值分解构造低阶的子空间,降低系统的自由度,并使用径向基函数对子空间进行近似,通过子空间的线性组合获得新的结构响应,实现基于MCS的快速不确定量化分析。考虑不同荷载状况下,结构形状参数和材料属性参数对应力强度因子的影响,使用改进的MCS计算应力强度因子的统计特征,量化不确定参数对结构的影响。最后通过若干算例验证了该算法的准确性和有效性。
