Study on Determination Methods of Important Landscapes along the Mainstream of Yellow River

According to the response relationship between landscape and water resource,the selection principle of important landscapes was determined from the perspectives of nature and history in this study,and determination methods or steps of important landscapes along the mainstream of Yellow River were also established to select important landscapes that should be protected.

Hu Foods and Production Methods in Qimin Yaoshu( Important Arts for the People's Welfare)

Qimin Yaoshu( Important Arts for the People's Welfare) made a detailed record of the diet and its production methods in the middle and lower reaches of the Yellow River during the Wei Dynasty.Hu foods are important parts in the book.Hu foods recorded in Important Arts for the People's Welfare mainly include cheese products,cake products,and dish products.These contents not only reflect the exchange of diet culture between different nationalities in the middle and lower reaches of the Yellow River during this period,but also reflect the breadth and depth of ethnic exchanges and integration in this period.

Importance Sampling Method in V-Space

Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.

Ranking important nodes in complex networks by simulated annealing

In this paper, based on simulated annealing a new method to rank important nodes in complex networks is presented.First, the concept of an importance sequence（IS） to describe the relative importance of nodes in complex networks is defined. Then, a measure used to evaluate the reasonability of an IS is designed. By comparing an IS and the measure of its reasonability to a state of complex networks and the energy of the state, respectively, the method finds the ground state of complex networks by simulated annealing. In other words, the method can construct a most reasonable IS. The results of experiments on real and artificial networks show that this ranking method not only is effective but also can be applied to different kinds of complex networks.

Divisia Decomposition Method and Its Application to Changes of Net Oil Import Intensity

The existing oil import dependence index cannot exactly measure the economic cost or scales, and it is difficult to describe the economical aspect of oil security. To measure the foreign dependence of one country's economy and reflect its oil economic security, this paper defines the net oil import intensity as the ratio of net oil import cost to GDP. By using Divisia Index Decomposition, the change of net oil import intensity in five industrialized countries and five newly industrialized countries during 1971—2010 is decomposed into five factors: oil price, oil intensity, oil self-sufficiency, domestic price level and exchange rate. The result shows that the dominating factors are oil price and oil intensity; moreover, the newly industrialized countries have higher net oil import intensity than industrialized countries.

2022 Multiple-country Monkeypox Outbreak and Its Importation Risk into China:An Assessment Based on the Risk Matrix Method

Objective To analyze the 2022 multiple-country monkeypox outbreak and assess its importation risk into China.Methods Data was from United States Centers for Disease Control and Prevention.We described the global epidemic and calculated concentration index to measure economic-related inequality.Importation risk into China was evaluated and ranked by using risk matrix method and Borda count method,respectively.Results As of July 29,2022,of 79 countries or territories,39(49.37%,39/79),17(21.52%,17/79),6(7.59%,6/79),12(15.19%,12/79),and 5(6.33%,5/79)country or territories identified cases<10,10-,51-,101-,and>1,000.There were economic-related health disparities exist in the distribution of cases(the concentration index=0.42,P=0.027),and the inequality disadvantageous to the rich(pro-poor).There were 12(15.38%,12/78),15(19.23%,15/78),6(7.69%,6/78),and 45(57.69%,45/78)countries or territories with extremely high,high,moderate,and low importation risk.United States and France ranked first with the highest Borda points of 156,and counts of zero.Conclusion Of 78 countries or territories,the key attention need be paid to the United States and France,relatively.As the epidemic progresses,preparing prevention and control measures to further reduce importation risk was crucial.

Subinterval Decomposition-Based Interval Importance Analysis Method

The importance analysis method represents a powerful tool for quantifying the impact of input uncertainty on the output uncertainty.When an input variable is described by a specific interval rather than a certain probability distribution,the interval importance measure of input interval variable can be calculated by the traditional non-probabilistic importance analysis methods.Generally,the non-probabilistic importance analysis methods involve the Monte Carlo simulation(MCS)and the optimization-based methods,which both have high computational cost.In order to overcome this problem,this study proposes an interval important analytical method avoids the time-consuming optimization process.First,the original performance function is decomposed into a combination of a series of one-dimensional subsystems.Next,the interval of each variable is divided into several subintervals,and the response value of each one-dimensional subsystem at a specific input point is calculated.Then,the obtained responses are taken as specific values of the new input variable,and the interval importance is calculated by the approximated performance function.Compared with the traditional non-probabilistic importance analysis method,the proposed method significantly reduces the computational cost caused by the MCS and optimization process.In the proposed method,the number of function evaluations is equal to one plus the sum of the subintervals of all of the variables.The efficiency and accuracy of the proposed method are verified by five examples.The results show that the proposed method is not only efficient but also accurate.

Global Epidemic of Ebola Virus Disease and the Importation Risk into China: An Assessment Based on the Risk Matrix Method

Objective To analyze the global epidemic status of the Ebola virus disease(EVD) and assess the importation risk into China.Methods Data from World Health Organization reports were used. We described the global epidemic status of EVD from 1976–2021, and assessed and ranked the importation risk of EVD from the diseaseoutbreaking countries into China using the risk matrix and Borda count methods, respectively.Results From 1976–2021, EVD mainly occurred in western and central Africa, with the highest cumulative number of cases(14,124 cases) in Sierra Leone, and the highest cumulative fatality rate(85%) in the Congo. Outbreaks of EVD have occurred in the Democratic Republic of the Congo and Guinea since 2018. The importation risk into China varies across countries with outbreaks of disease.The Democratic Republic of the Congo had an extremely high risk(23 Borda points), followed by Guinea and Liberia. Countries with a moderate importation risk were Nigeria, Uganda, Congo, Sierra Leone,Mali, and Gabon, while countries with a low importation risk included Sudan, Senegal, and Co te d’Ivoire.Conclusion China is under the risk of EVD importation with the globalization and severe epidemic status of EVD. Key attention need to be paid to the Democratic Republic of the Congo, Guinea, and Liberia. Therefore, it is necessary to prevent and prepare in advance for importation risk in China.

Numerical Study of φ^4 Model by Potential Importance Sampling Method

We investigate the phenomena of spontaneous symmetry breaking for φ^4 model on a square lattice in the parameter space by using the potential importance samplingmethod, which was proposed by Milchev, Heermann, and Binder [J. Star. Phys. 44 （1986） 749]. The critical values of the parameters allow us to determine the phase diagram of the model. At the same time, some relevant quantifies such as susceptibility and specific heat are also obtained.

On Solving a System of Volterra Integral Equations with Relaxed Monte Carlo Method

A random simulation method was used for treatment of systems of Volterra integral equations of the second kind. Firstly, a linear algebra system was obtained by discretization using quadrature formula. Secondly, this algebra system was solved by using relaxed Monte Carlo method with importance sampling and numerical approximation solutions of the integral equations system were achieved. It is theoretically proved that the validity of relaxed Monte Carlo method is based on importance sampling to solve the integral equations system. Finally, some numerical examples from literatures are given to show the efficiency of the method.

基于自动重要抽样方法的减方差技巧体系构建与验证

屏蔽计算问题根据求解目标不同一般可分为源-探测器问题、区域问题和全局问题。MCShield研究团队针对3类问题中存在的深穿透问题提出了相应的减方差技巧,本文以此为基础构建了基于自动重要抽样(AIS)方法的减方差技巧体系,并开展了验证工作。针对源-探测器问题,采用NUREG/CR-6115 PWR压力容器计算基准题对小探测器自动重要抽样(SDAIS)方法进行验证。结果表明,SDAIS方法的计算效率约为AIS方法的7倍。此外还提出并验证了基于AIS伴随蒙特卡罗的耦合减方差(AIS-CADIS)方法,将AIS方法引入到蒙特卡罗伴随计算中,取得了良好的效果。针对全局问题,提出网格化-AIS方法并使用简化反应堆屏蔽计算算例进行验证,结果表明,网格化-AIS方法的计算效率是AIS方法的12倍左右,是直接蒙特卡罗方法的290倍左右。

引入重要度修正因子的复杂光电系统可靠性分配研究

以某新型复杂光电系统为研究对像,针对传统评分分配法客观性差、分配偏差大的缺点,构建重要度修正因子,提出了一种引入重要度修正因子的可靠性评分分配法。首先,运用模糊层次分析法,得到功能单元对上级功能单元/系统可靠性影响的相对重要度;然后,基于相对重要度,按照专家评分规则,得到功能单元对上级功能单元/系统可靠性影响的绝对重要度;最后,基于相对重要度和绝对重要度,构建功能单元重要度修正因子,以此修正各功能单元的评分结果。经对比验证,关重功能单元可靠性分配值较传统评分分配值至少提高6%,引入重要度修正因子的评分分配法能有效削弱传统评分分配法的主观影响,释放关重功能单元可靠性余量,提高功能单元可靠性分配的科学性、合理性,进而提高复杂系统可靠性设计水平。

深穿透跨尺度辐射场分析软件NECP-MCX研发及应用

西安交通大学核工程计算物理实验室自主研发了深穿透跨尺度辐射场分析软件NECP-MCX。针对大空间伽马射线辐射输运模拟、聚变堆停堆剂量模拟和点源屏蔽问题等新应用场景下的新问题与新挑战,在NECP-MCX中研发了对应的新方法与新功能。针对km尺度的伽马射线辐射输运问题,提出一致性共轭驱动重要性抽样(CADIS)-下次事件估计器(NEE)耦合方法,该方法能够精确高效地获得km尺度距离处的光子通量密度,计算效率比传统的NEE高6.8倍;针对聚变堆停堆剂量问题,采用粒子输运-燃耗-活化-源项耦合分析方法,获得PF线圈、TF线圈、真空室和偏滤器处停堆剂量随停堆时间的变化;对于点源屏蔽问题,提出首次碰撞源(FCS)-CADIS方法,解决CADIS方法对点源进行源偏倚的局限性,FCS-CADIS方法的计算效率比CADIS方法高2倍。

基于多目标狼群算法的机场行李导入系统仿真优化研究

针对民航机场行李导入系统运行过程中旅客行李注入等待时间长、系统能耗高等问题,综合考虑虚拟视窗控制方式、收集带式输送机运行速度、虚拟视窗长度及同时开放值机柜台数量等关键控制参数对机场行李导入系统运行效率的影响,提出一种求解该问题的仿真优化框架。通过分析机场行李导入系统实际运行工况,建立参数化仿真优化模型。以最小化旅客行李注入平均等待时间和系统能耗为优化目标,结合系统设计和运行过程中的实际约束条件,建立该问题的数学模型,并设计了一种多目标自适应并行狼群算法进行求解。该算法针对所提问题特性及经典狼群算法易陷入局部最优和收敛速度慢等不足,提出一种混合整实数单链编码方式,融合反向学习策略生成初始种群,引入自适应游走概率机制和智能行为并行机制,采用局部和全局自适应邻域搜索及启发式保优策略实现狼群算法智能行为搜索,使用Pareto非支配排序进行寻优迭代并获得最优解集。以国内某大型国际航空枢纽机场行李导入系统为例设计不同规模多种算法对比实验,验证了所提方法的有效性和优越性。

奥运奖牌可以被预测吗?——基于可解释机器学习视角

基于1992-2021年夏季奥运会的分项目成绩大数据,使用随机森林模型评估不同项目金牌和奖牌的可预测性,发现各项目存在较大的差异:对奖牌而言,可预测性最强的是乒乓球、羽毛球和游泳,而最弱的是水球、现代五项和排球。基于可解释机器学习方法挖掘社会经济因素对奥运奖牌的影响发现:(1)对同一个项目而言,女子项目的可预测准确性普遍高于男子项目;(2)代表队所在地区的人口规模、人均GDP、是否为主办国等因素对奖牌总数具有一定影响;(3)在特定项目上,代表队的传统优势(如中国的乒乓球、美国的田径等)对奖牌预测具有较大影响。

融合节点重要性的通信系统无特征网络链路预测方法

通信系统的无特征网络链路中,由于忽略了节点的特征属性,导致预测评估结果的曲线下面积(Area Under Curve,AUC)值较低。针对上述现象,提出融合节点重要性的通信系统链路预测方法。提取无特征网络中节点的局部特征,构建节点的时间序列数据。计算每个节点的重要性,利用节点的重要性和时间序列数据,通过特定的算法,获取每个节点的预测值,从而实现无特征网络链路的预测。实验结果表明,该方法预测评估结果的AUC值较高,能够更准确地预测网络中的链路连接。

我国城市数字创业活跃度与外部驱动因素

数字创业是数字技术与数字经济发展的产物,是数字化赋能经济高质量发展的关键路径,客观认识数字创业现状、揭示其驱动因素是激发数字创业活力的前提。基于2006—2021年我国283个地级及以上城市(未含香港、澳门、台湾地区城市)信息传输、软件和信息技术服务业新注册企业数据,测算分析数字创业活跃度水平及其变化,进而利用随机森林模型估计数字创业活跃度多维外部驱动因素重要性。数字创业活跃度测算结果表明,我国城市数字创业活跃度水平呈先下降后上升的V字形变化趋势,主要城市数字创业活跃度水平明显高于其他城市,且两者的差距有扩大趋势。外部驱动因素分析结果表明,我国城市数字创业活跃度受技术环境、市场环境、经济环境、政策环境维度因素共同影响,其中产业发展基础、政府支持、技术累积量、市场化程度、产业结构是主要驱动因素;分阶段看,技术累积量和人力资本水平的驱动作用在增强,市场规模的驱动作用在减弱;分城市类型看,相比于主要城市,技术环境维度的科研投入强度、人力资本水平、融资条件,特别是市场环境维度的市场化程度对其他城市的驱动作用更强。为提升我国城市数字创业活跃度,应加强政策引导,加大保障力度,着力推动数字创业;健全要素市场运行机制,优化数字创业市场环境;围绕产业发展引进和培养人才,加强数字人才队伍建设;畅通创业融资渠道,缓解企业资金困境。

Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

The complex sand-casting process combined with the interactions between process parameters makes it difficult to control the casting quality,resulting in a high scrap rate.A strategy based on a data-driven model was proposed to reduce casting defects and improve production efficiency,which includes the random forest(RF)classification model,the feature importance analysis,and the process parameters optimization with Monte Carlo simulation.The collected data includes four types of defects and corresponding process parameters were used to construct the RF model.Classification results show a recall rate above 90% for all categories.The Gini Index was used to assess the importance of the process parameters in the formation of various defects in the RF model.Finally,the classification model was applied to different production conditions for quality prediction.In the case of process parameters optimization for gas porosity defects,this model serves as an experimental process in the Monte Carlo method to estimate a better temperature distribution.The prediction model,when applied to the factory,greatly improved the efficiency of defect detection.Results show that the scrap rate decreased from 10.16% to 6.68%.

基于神经网络的粒子输运问题高效计算方法

蒙特卡罗方法是求解粒子输运问题的有力工具之一,其局限性在于为达到精度要求需模拟大量粒子,计算耗时长,这阻碍了该方法的进一步应用,尤其在需快速响应的情形.本文结合神经网络和若干蒙特卡罗方法基本原理发展了一种计算方法,能够实现源分布可变,几何、材料和目标计数不变的中子输运问题的快速准确求解.首先,为高效生成用于神经网络训练的数据,利用重要性原理实现在同样模拟次数基础上有效扩充训练数据集容量,在一定程度上克服了使用蒙特卡罗计算获取训练数据耗时长的缺点.进而,基于目标计数是源分布与重要性函数乘积积分的事实,设计了利用神经网络实现快速输运计算的策略.该网络的输入是中子源项,输出是目标计数,在几何、材料和目标计数固定的情况下,该神经网络可重复使用,根据新的源项快速准确得到目标计数.本文所提出方法的原理和框架同样适用于其他种类粒子的同类型输运问题.基于若干基准模型的验证表明,训练得到的神经网络能在不到1 s的时间内得到目标计数,且与蒙特卡罗大样本模拟得到基准结果的平均相对偏差均低于5%.

函数展开计数在CLUTCH方法中的初步应用

反复裂变几率(IFP)方法广泛应用于求解k特征值对连续能量核数据的灵敏度系数,然而IFP方法存在内存占用大的问题,因此CLUTCH方法被提出以解决该问题。但对于大规模问题,如压水堆全堆问题,基于网格的CLUTCH(CLUTCH-Mesh)方法存在权重函数不易收敛的问题。本文采用函数展开计数(FET)方法对CLUTCH方法中的权重函数进行统计(CLUTCH-FET)以解决该问题,函数展开计数选取的基函数是勒让德多项式。本文在蒙特卡罗粒子输运计算程序NECP-MCX中实现了IFP、CLUTCH-Mesh和CLUTCH-FET 3种方法,以IFP方法的计算结果作为参考解,对CLUTCH-Mesh和CLUTCH-FET方法的精度和效率进行了验证。数值结果表明:对于小规模问题,如Godiva和Flattop问题,CLUTCH-Mesh和CLUTCH-FET方法具有与IFP方法相当的精度,且计算效率较IFP方法更高;对于大规模问题,如AP1000全堆问题,CLUTCH-Mesh方法的计算精度下降,而CLUTCH-FET方法可保持较高的精度和计算效率,CLUTCH-FET方法的品质因子较IFP方法和CLUTCH-Mesh方法分别最多提高了5.2和6.0倍。