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Combining Random Forest and Monte Carlo Method to Determine the Driving Factors and Uncertainty of Forest Age Prediction in Northwest China 认领 引用 被引量：1
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作者 ZENG Jia LIU Jincheng +1 位作者 LI Limin KHAN Tauheed Ullah 《Chinese Geographical Science》 SCIE CAS CSCD 2026年第1期144-156,I0004-I0007,共13页
Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have becom... Stand age plays a crucial role in forest biomass estimation and carbon cycle modeling.Assessing the uncertainty of stand age prediction models and identifying the key driving factors in the modeling process have become major challenges in forestry research.In this study,we selected the Shaanxi-Gansu-Ningxia region of Northeast China as the research area and utilized multi-source datasets from the summer of 2019 to extract information on spectral,textural,climatic,water balance,and stand characteristics.By integrating the Random Forest(RF)model with Monte Carlo(MC)simulation,we constructed six regression models based on different combina-tions of features and evaluated the uncertainty of each model.Furthermore,we investigated the driving factors influencing stand age modeling by analyzing the effects of different types of features on age inversion.Model performance and accuracy were assessed using the root mean square error(RMSE),mean absolute error(MAE),and the coefficient of determination(R2),while the relative root mean square error(rRMSE)was employed to quantify model uncertainty.The results indicate that the scenarios with more obvious improve-ment in accuracy and effective reduction in uncertainty were Scenario 3 with the inclusion of climate and water balance information(RMSE=25.54 yr,MAE=18.03 yr,R2=0.51,rRMSE=19.17%)and Scenario 5 with the inclusion of stand characterization informa-tion(RMSE=18.47 yr,MAE=13.05 yr,R2=0.74,rRMSE=16.99%).Scenario 6,incorporating all feature types,achieved the highest accuracy(RMSE=17.60 yr,MAE=12.06 yr,R2=0.77,rRMSE=14.19%).In this study,elevation,minimum temperature,and diameter at breast height(DBH)emerged as the key drivers of stand-age modeling.The proposed method can be used to identify drivers and to quantify uncertainty in stand-age estimation,providing a useful reference for improving model accuracy and uncertainty assessment. 展开更多
关键词 stand age Randon Forest(RF)model Monte Carlo(MC)method Sentinel-2 National Forest Inventory(NFI) Shaanxi-Gansu-Ningxia(SGN),Northwest China
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Monte Carlo simulation method for estimating the fine rattler fraction in large-ratio binary mixtures 认领 引用
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作者 Jing WANG Changyu SHI Daosheng LING 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第3期231-245,共15页
Reliable estimation of the fine particle rattler fraction is crucial for understanding the structural and mechanical responses of binary granular systems with large size ratios.However,such estimation is challenged by... Reliable estimation of the fine particle rattler fraction is crucial for understanding the structural and mechanical responses of binary granular systems with large size ratios.However,such estimation is challenged by the general inability to obtain interparticle contact force information directly from experimental images and by the lower accuracy of positional and size identification of fine particles compared with coarse particles.To address these challenges,in this study,we focused on 2D bidisperse granular assemblies with large size ratios(α=7,9,12,and 16)and developed an approach based on Monte Carlo simulation(MCS)that relies solely on the size and positional information of coarse particles,avoiding the need for force-resolved computations.The performance of the method was evaluated against experimental measurements and discrete element method(DEM)simulations.The MCS-based predictions show close agreement with experimental results,with a slight overall overestimation.At low fines content,the approach tends to overestimate the fine particle rattler fraction relative to DEM results,whereas at higher fines content,it underestimates the rattler fraction.Overall,the proposed MCS-based approach enables robust and relatively accurate estimation of the fine particle rattler fraction.This study provides a practical framework for predicting the rattler fraction,contributes to advancing both experimental analysis and theoretical modeling in granular physics,and demonstrates the conceptual extendibility of the MCS framework to more complex 3D packings. 展开更多
关键词 Granular materials Rattlers Fines content Size ratio Discrete element method(DEM) Monte Carlo
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Probabilistic Rock Slope Stability Assessment of Heterogeneous Pyroclastic Slopes Considering Collapse Using Monte Carlo Methodology 认领 引用
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作者 Miguel A.Millán Rubén A.Galindo Fausto Molina-Gómez 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第9期2923-2941,共19页
Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patte... Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making. 展开更多
关键词 Pyroclast Monte Carlo rock slope volcanic rock discontinuity layout optimization method non-homogeneous slope spatial variability
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Adaptive reverse Monte Carlo method and evaluation for infrared radiation characteristics of scramjet 认领 引用
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作者 Xinyuan LIU Yongqiang SHI +3 位作者 Qingzhen YANG Huicheng YANG Xubo DU Xufei WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第8期187-203,共17页
Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work pr... Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work proposes an Adaptive Reverse Monte Carlo(ARMC)method and develops an analytical model for the IR radiation of scramjet considering gaseous kerosene and hydrogen fueled conditions.The evaluation studies show that at a global equivalence ratio of 0.8,the IR radiation from hydrogen-fueled plume is predominantly from H2O and spectral peak is 1.53 kW·Sr-1·μm-1at the 2.7μm band,while the kerosene-fueled plume exhibits a spectral intensity approaching 7.0 kW·Sr-1·μm-1at the 4.3μm band.At the backward detection angle,both types of scramjets exhibit spectral peaks within the 1.3-1.4μm band,with intensities around10 kW·Sr-1·μm-1.The integral radiation intensity of hydrogen-fueled scramjet is generally higher than kerosene-fueled scramjet,particularly in 1-3μm band.Meanwhile,at wide detection angles,the solid walls become the predominant radiation source.The radiation intensity is highest in1-3μm and weakest in 8-14μm band,with values of 21.5 kW·Sr-1and 0.57 kW·Sr-1at the backward detection angles,respectively.Significant variations in the radiation contributions from gases and solids are observed across different bands under the two fuel conditions,especially within 3-5μm band.This research provides valuable insights into the IR radiation characteristics of scramjets,which can aid in the development of IR detection systems for AHV. 展开更多
关键词 Hypersonic Infrared radiation Monte Carlo methods Scramjet Statistical variance
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基于Monte-Carlo的弃渣场可靠度分析 认领 引用
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作者 董福 李鹏 王武钢 《陕西水利》 2026年第2期6-9,共4页
弃渣在堆积过程中由于其颗粒大小不均匀,致使其不同部位取样测得的参数值具有空间差异性。为研究降雨对紫阳县一处弃渣场稳定性的影响,在现场勘查及取样试验的基础上考虑弃渣在堆积过程中内摩擦角和粘聚力的随机性,并借助Geo-Studio软... 弃渣在堆积过程中由于其颗粒大小不均匀,致使其不同部位取样测得的参数值具有空间差异性。为研究降雨对紫阳县一处弃渣场稳定性的影响,在现场勘查及取样试验的基础上考虑弃渣在堆积过程中内摩擦角和粘聚力的随机性,并借助Geo-Studio软件对边坡在不同降雨条件下的稳定性进行可靠度分析。得出不同条件下该边坡失效的概率及稳定系数,以此来弥补单纯数值计算的缺陷,提高边坡稳定性预测的准确性,可为该弃渣场后续治理工程提供一定的参考依据。 展开更多
关键词 弃渣场 可靠度分析 Monte-Carlo Geo-Studio
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Mie-T矩阵耦合的沙尘多次散射效应表征与Monte Carlo验证 认领 引用
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作者 汤牧云 朝克夫 +1 位作者 华文成 崔存森 《中国光学（中英文）》 EI CAS CSCD 北大核心 2026年第1期85-95,共11页
为精确量化沙尘天气对城市光电系统可见光传输的衰减影响,本研究以呼和浩特地区为例,构建了融合非球形粒子修正的光传输预测模型。基于Mie散射理论,结合本地沙尘样品的扫描电镜与能谱分析数据,计算三基色红绿蓝波段的沙尘粒子消光特性;... 为精确量化沙尘天气对城市光电系统可见光传输的衰减影响,本研究以呼和浩特地区为例,构建了融合非球形粒子修正的光传输预测模型。基于Mie散射理论,结合本地沙尘样品的扫描电镜与能谱分析数据,计算三基色红绿蓝波段的沙尘粒子消光特性;进而采用T矩阵法对非球形粒子的散射参数进行修正,并利用Monte Carlo方法模拟光子的多次散射过程,系统比较单次与多次散射模型下的衰减率差异。结果表明,单次散射模型会系统性高估衰减率,蓝光波段最大误差达18.3%;经多次散射修正后,衰减率平均降低12.4%。在本例中,能见度为400 m,蓝光衰减率约为95 dB/km,显著高于红光的衰减率(约70 dB/km)。本研究构建的混合模型显著提升了沙尘环境下可见光衰减的预测精度,明确多次散射效应的关键影响,为城市光电系统在沙尘天气下的可见光传输提供了可靠的理论依据与数据支持。 展开更多
关键词 沙尘天气 消光系数 Mie散射理论 T矩阵法 Monte Carlo模拟 可见光
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中国移民研究的问题与方法——Carlos Rojas(罗鹏)教授访谈录 认领 引用
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作者 张惠苑 《华文文学》 2026年第2期116-121,共6页
罗鹏教授是近年来海外汉学界最为活跃的学者之一。他常年在美国杜克大学中东与亚洲研究中心开设一门研究生课程:“中国的移民与流散”(Chinese Migration and Diaspora)。本次访谈以这门课为基础,主要从移民研究的背景、对象与反思方式... 罗鹏教授是近年来海外汉学界最为活跃的学者之一。他常年在美国杜克大学中东与亚洲研究中心开设一门研究生课程:“中国的移民与流散”(Chinese Migration and Diaspora)。本次访谈以这门课为基础,主要从移民研究的背景、对象与反思方式等几个方面,展开对罗鹏教授的访谈。罗鹏教授对中国移民问题的研究兴趣,源于《镜花缘》中的“离乡病”。他的研究对象涵盖了中国的跨国移民和内部的流动人口。谈到内部流动人口问题,他关注到户籍制度与经济因素作用在“流动人口”的生存境遇中产生的矛盾与冲突。本次访谈,罗鹏教授在跨学科的语境中,运用文化研究的方法进行思考,也给我们在研究方法上带来启发。 展开更多
关键词 罗鹏 移民研究 问题 方法
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一种采用Monte-Carlo积分的局部最大熵估计方案 认领 引用
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作者 周慧 《计算力学学报》 CAS CSCD 北大核心 2026年第2期324-331,共8页
局部最大熵估计方案是一种基于最大熵原理的无网格法。文献[1]用β=γh2调参使得λ收敛,本文将参数β由标量拓展为节点i上的倒格矢矩阵βi,同样使得λ收敛。基于文献[2],引入材料的非均匀性,强调了局部最大熵估计是跨尺度模拟的... 局部最大熵估计方案是一种基于最大熵原理的无网格法。文献[1]用β=γh2调参使得λ收敛,本文将参数β由标量拓展为节点i上的倒格矢矩阵βi,同样使得λ收敛。基于文献[2],引入材料的非均匀性,强调了局部最大熵估计是跨尺度模拟的重要方法。在宏观尺度的应用中,有别于常用的高斯积分法,本文使用Monte-Carlo积分避免等参变换的雅可比矩阵求逆,达到了无网格的目的,其应用在线弹性力学的算例中得到了合理的近似解。 展开更多
关键词 局部最大熵估计方案 Monte-Carlo积分 无网格法
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HIGH ORDER PROBABILISTIC NUMERICAL METHODS FOR FORWARD BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS 认领 引用
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作者 Qiang Han Yurong Liu 《Journal of Computational Mathematics》 SCIE CSCD 2026年第6期1631-1661,共31页
In this paper,we design novel high order probabilistic numerical algorithms for forward backward stochastic differential equations.Moreover,we derive the error estimates and prove the high order convergence rates of t... In this paper,we design novel high order probabilistic numerical algorithms for forward backward stochastic differential equations.Moreover,we derive the error estimates and prove the high order convergence rates of the proposed schemes.Because the proposed scheme involves conditional expectations,an estimator based on the multilevel Monte Carlo method is applied to approximate the conditional expectations.Furthermore,we theoretically demonstrate that the computational complexity of our numerical method is proportional to the square of prescribed accuracy.Numerical experiments are given to illustrate the theoretical results. 展开更多
关键词 Forward Backward Stochastic Differential Equation Probabilistic Numerical Method Multilevel Monte Carlo Computational Complexity High Order Discretization
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基于Monte-Carlo模拟典型台风情景下的低矮房屋易损性分析 认领 引用
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作者 林美静 田鹏波 《城市勘测》 2026年第2期121-127,共7页
台风灾害是我国东南沿海地区最常见的自然灾害之一,对低矮房屋的安全构成严重威胁,其造成的损失也具有极大不确定性,基于情景构建评估灾害损失是近年来的研究热点之一。本文从情景构建的角度,根据台风历史案例数据对其特征参数进行模拟... 台风灾害是我国东南沿海地区最常见的自然灾害之一,对低矮房屋的安全构成严重威胁,其造成的损失也具有极大不确定性,基于情景构建评估灾害损失是近年来的研究热点之一。本文从情景构建的角度,根据台风历史案例数据对其特征参数进行模拟,分别采用EM算法和Weibull拟合描述台风路径及中心气压差等随机变量型情景要素构建典型台风情景。以广东省为例,构建了三类台风路径下各地区低矮房屋受损情景,采用Monte-Carlo结合建筑构件安全的模拟方法,分析典型情景下的不同空间位置的房屋易损性,并通过分析模拟结果的统计特征,讨论台风对不同瓦片类型低矮房屋的影响特征,为台风灾害应急管理提供新思路。 展开更多
关键词 台风灾害 房屋易损性 Monte-Carlo方法 情景构建 不确定性
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Forced propagation method for Monte Carlo fission source convergence acceleration in the RMC 认领 引用 被引量：6
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作者 Ze-Guang Li Kan Wang +1 位作者 Yu-Chuan Guo Xiao-Yu Guo 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2021年第3期52-62,共11页
In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various accelerati... In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various acceleration methods have been developed,some methods cannot reduce convergence times,whereas others have been limited to specific problem geometries.In this study,a new fission source convergence acceleration(FSCA)method,the forced propagation(FP)method,has been proposed,which forces the fission source to propagate and accelerate fission source convergence.Additionally,some stabilization techniques have been designed to render the method more practical.The resulting stabilized method was then successfully implemented in the MC transport code,and its feasibility and effectiveness were tested using the modified OECD/NEA,one-dimensional slab benchmark,and the Hoogenboom full-core problem.The comparison results showed that the FP method was able to achieve efficient FSCA. 展开更多
关键词 Fission source convergence acceleration Monte Carlo method Forced propagation method RMC code
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Monte Carlo Method for the Uncertainty Evaluation of Spatial Straightness Error Based on New Generation Geometrical Product Specification 认领 引用 被引量：10
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作者 WEN Xiulan XU Youxiong +2 位作者 LI Hongsheng WANG Fenglin SHENG Danghong 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2012年第5期875-881,共7页
Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the resul... Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear. 展开更多
关键词 uncertainty evaluation Monte Carlo method spatial straightness error quasi particle swarm optimization minimum zone solution geometrical product specification
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Statistical Modification Analysis of Helical Planetary Gears based on Response Surface Method and Monte Carlo Simulation 认领 引用 被引量：16
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作者 ZHANG Jun GUO Fan 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2015年第6期1194-1203,共10页
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random error... Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system＇s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error（DTE） fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system＇s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously. 展开更多
关键词 tooth modification helical planetary gears response surface method Monte Carlo simulation
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Monte Carlo Simulation of Fractures Using Isogeometric Boundary Element Methods Based on POD-RBF 认领 引用 被引量：3
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作者 Haojie Lian Zhongwang Wang +3 位作者 Haowen Hu Shengze Li Xuan Peng Leilei Chen 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第7期1-20,共20页
This paper presents a novel framework for stochastic analysis of linear elastic fracture problems.Monte Carlo simulation(MCs)is adopted to address the multi-dimensional uncertainties,whose computation cost is reduced ... This paper presents a novel framework for stochastic analysis of linear elastic fracture problems.Monte Carlo simulation(MCs)is adopted to address the multi-dimensional uncertainties,whose computation cost is reduced by combination of Proper Orthogonal Decomposition(POD)and the Radial Basis Function(RBF).In order to avoid re-meshing and retain the geometric exactness,isogeometric boundary element method(IGABEM)is employed for simulation,in which the Non-Uniform Rational B-splines(NURBS)are employed for representing the crack surfaces and discretizing dual boundary integral equations.The stress intensity factors(SIFs)are extracted by M integral method.The numerical examples simulate several cracked structures with various uncertain parameters such as load effects,materials,geometric dimensions,and the results are verified by comparison with the analytical solutions. 展开更多
关键词 Monte Carlo simulation POD RBF isogeometric boundary element method fracture
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Elbow precision machining technology by abrasive flow based on direct Monte Carlo method 认领 引用 被引量：4
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作者 LI Jun-ye ZHU Zhi-bao +4 位作者 WANG Bin-yu ZHANG Xin-ming WANG Fei ZHAO Wei-hong XU Cheng-yu 《Journal of Central South University》 SCIE EI CAS CSCD 2020年第12期3667-3683,共17页
The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and ... The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology. 展开更多
关键词 precision machining by abrasive flow direct simulation Monte Carlo method abrasive particle collision processing technology
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Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method 认领 引用 被引量：10
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作者 Ataei Mohammad Shahsavany Hashem Mikaeil Reza 《International Journal of Mining Science and Technology》 EI CAS 2013年第4期561-566,共6页
One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developi... One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked. 展开更多
关键词 Multi-criteria decision making AHP Monte Carlo simulation Mining method selection
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Seismic fluid identification using a nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo method 认领 引用 被引量：6
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作者 Guang-Zhi Zhang Xin-Peng Pan +2 位作者 Zhen-Zhen Li Chang-Lu Sun Xing-Yao Yin 《Petroleum Science》 SCIE CAS CSCD 2015年第3期406-416,共11页
Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain M... Elastic impedance inversion with high efficiency and high stability has become one of the main directions of seismic pre-stack inversion. The nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo （MCMC） method is proposed in this paper, combining conventional MCMC method based on global optimization with a preconditioned conjugate gradient （PCG） algorithm based on local optimization, so this method does not depend strongly on the initial model. It converges to the global optimum quickly and efficiently on the condition that effi- ciency and stability of inversion are both taken into consid- eration at the same time. The test data verify the feasibility and robustness of the method, and based on this method, we extract the effective pore-fluid bulk modulus, which is applied to reservoir fluid identification and detection, and consequently, a better result has been achieved. 展开更多
关键词 Elastic impedance Nonlinear inversion FastMarkov chain Monte Carlo method - Preconditionedconjugate gradient algorithm ~ Effective pore-fluid bulkmodulus
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Research on Equipment Support Activity Process Simulation Based on Monte Carlo Method 认领 引用 被引量：2
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作者 XING Biao SONG Tailiang +2 位作者 CAO Junhai DONG Yuansheng LI Kai 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第2期250-255,共6页
The influencing factors of the equipment support activity process have the characteristics of nonlinearity, high dimension, many constraints, random uncertainty and fuzzy uncertainty. Monte Carlo method can solve the ... The influencing factors of the equipment support activity process have the characteristics of nonlinearity, high dimension, many constraints, random uncertainty and fuzzy uncertainty. Monte Carlo method can solve the above problems commendably. This paper analyzes the main equipment support activity process and establishes the sampling plan and simulation model of the medium maintenance process based on Monte Carlo method, and the simulation result verifies a fact that the medium maintenance time can be effectively reduced when parallel operation on some procedures is used. It has a practical value and can give good advice to achieve the capability of equipment supportability. 展开更多
关键词 Monte Carlo method equipment support activity process simulation
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Comparison of GUF and Monte Carlo methods to evaluate task-specific uncertainty in laser tracker measurement 认领 引用 被引量：2
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作者 杨景照 李国喜 +2 位作者 吴宝中 龚京忠 王杰 《Journal of Central South University》 SCIE EI CAS 2014年第10期3793-3804,共12页
Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplemen... Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplement, the Monte Carlo method, were used to estimate the uncertainty of task-specific laser tracker measurements. First, the sources of error in laser tracker measurement were analyzed in detail, including instruments, measuring network fusion, measurement strategies, measurement process factors(such as the operator), measurement environment, and task-specific data processing. Second, the GUM and Monte Carlo methods and their application to laser tracker measurement were presented. Finally, a case study involving the uncertainty estimation of a cylindricity measurement process using the GUF and Monte Carlo methods was illustrated. The expanded uncertainty results(at 95% confidence levels) obtained with the Monte Carlo method are 0.069 mm(least-squares criterion) and 0.062 mm(minimum zone criterion), respectively, while with the GUM uncertainty framework, none but the result of least-squares criterion can be got, which is 0.071 mm. Thus, the GUM uncertainty framework slightly underestimates the overall uncertainty by 10%. The results demonstrate that the two methods have different characteristics in task-specific uncertainty evaluations of laser tracker measurements. The results indicate that the Monte Carlo method is a practical tool for applying the principle of propagation of distributions and does not depend on the assumptions and limitations required by the law of propagation of uncertainties(GUF). These features of the Monte Carlo method reduce the risk of an unreliable measurement of uncertainty estimation, particularly in cases of complicated measurement models, without the need to evaluate partial derivatives. In addition, the impact of sampling strategy and evaluation method on the uncertainty of the measurement results can also be taken into account with Monte Carlo method, which plays a guiding role in measurement planning. 展开更多
关键词 task-specific uncertainty laser tracker measurement uncertainty evaluation Monte Carlo method uncertainy framework（GUF）
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Monte Carlo method for evaluation of surface emission rate measurement uncertainty 认领 引用 被引量：1
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作者 Yuan-Qiao Li Min Lin +4 位作者 Li-Jun Xu Rui Luo Yu-He Zhang Qian-Xi Ni Yun-Tao Liu 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第7期126-136,共11页
The aim of this study is to evaluate the uncertainty of 2πα and 2πβ surface emission rates using the windowless multiwire proportional counter method.This study used the Monte Carlo method (MCM) to validate the co... The aim of this study is to evaluate the uncertainty of 2πα and 2πβ surface emission rates using the windowless multiwire proportional counter method.This study used the Monte Carlo method (MCM) to validate the conventional Guide to the Expression of Uncertainty in Measurement (GUM) method.A dead time measurement model for the two-source method was established based on the characteristics of a single-channel measurement system,and the voltage threshold correction factor measurement function was indirectly obtained by fitting the threshold correction curve.The uncertainty in the surface emission rate was calculated using the GUM method and the law of propagation of uncertainty.The MCM provided clear definitions for each input quantity and its uncertainty distribution,and the simulation training was realized with a complete and complex mathematical model.The results of the surface emission rate uncertainty evaluation for four radioactive plane sources using both methods showed the uncertainty’s consistency En<0.070 for the comparison of each source,and the uncertainty results of the GUM were all lower than those of the MCM.However,the MCM has a more objective evaluation process and can serve as a validation tool for GUM results. 展开更多
关键词 Surface emission rate Monte Carlo method Metrology Probability distribution function Dead time Low-energy loss correction Least-squares method
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