Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Diffusion mechanism simulation of cloud manufacturing complex network based on cooperative game theory

Cloud manufacturing is a specific implementation form of the "Internet + manufacturing" strategy. Why and how to develop cloud manufacturing platform(CMP), however, remains the key concern of both platform operators and users. A microscopic model is proposed to investigate advantages and diffusion forces of CMP through exploration of its diffusion process and mechanism. Specifically, a three-stage basic evolution process of CMP is innovatively proposed. Then, based on this basic process, a more complex CMP evolution model has been established in virtue of complex network theory, with five diffusion forces identified. Thereafter, simulations on CMP diffusion have been conducted. The results indicate that, CMP possesses better resource utilization,user satisfaction, and enterprise utility. Results of simulation on impacts of different diffusion forces show that both the time required for CMP to reach an equilibrium state and the final network size are affected simultaneously by the five diffusion forces. All these analyses indicate that CMP could create an open online cooperation environment and turns out to be an effective implementation of the "Internet + manufacturing" strategy.

Application of Matter-element Model in Soil Nutrient Evaluation of Ecological Fragile Region

On the basis of the soil environment investigation in Da＇an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter （SOM）, total N （TN）, total P （TP）, total K （TK）, available N （AN）, available P （AP） and available K （AK） were chosen as the evaluation factors. A regional soil nutrient evaluation model was developed based on the matter-element model. The results show that the soil samples with nutrient grade Ⅱ-Ⅴ respectively account for 10%, 30%, 32.5% and 27.5%, and those with grade Ⅳ and Ⅴ account for 60% in all samples. The relationship between soil nutrients and land types indicates that the nutrients of farmland are relatively good, with 41.7% of soil samples with the nutrient grade Ⅳ and Ⅴ. The nutrients of saline-alkali land and sandy land are the worst, with 100% of soil samples with the nutrient grade IV and V. And the ratios of soil samples grade IV and V in grassland and wasteland are respectively 62.5 % and 54.55%. Generally speaking, the soil nutrients status in Da＇an City is poor, 60% of soil samples are in poor and extremely poor conditions, indicating that the soil has been severely eroded. Being a relatively superior evaluation method with more accurate resuits and spatial distribution consistency, matter-element analysis is more suitable for regional soil nutrient evaluation than previous models.

Multi-VMs Intrusion Detection for Cloud Security Using Dempster-shafer Theory

Cloud computing provides easy and on-demand access to computing resources in a configurable pool.The flexibility of the cloud environment attracts more and more network services to be deployed on the cloud using groups of virtual machines(VMs),instead of being restricted on a single physical server.When more and more network services are deployed on the cloud,the detection of the intrusion likes Distributed Denialof-Service(DDoS)attack becomes much more challenging than that on the traditional servers because even a single network service now is possibly provided by groups of VMs across the cloud system.In this paper,we propose a cloud-based intrusion detection system(IDS)which inspects the features of data flow between neighboring VMs,analyzes the probability of being attacked on each pair of VMs and then regards it as independent evidence using Dempster-Shafer theory,and eventually combines the evidence among all pairs of VMs using the method of evidence fusion.Unlike the traditional IDS that focus on analyzing the entire network service externally,our proposed algorithm makes full use of the internal interactions between VMs,and the experiment proved that it can provide more accurate results than the traditional algorithm.

Safety Risk Assessment of Overturning Construction of Towering Structure Based on Cloud Matter–Element Coupled Model

Rapid urbanization has led to a surge in the number of towering structures,and overturning is widely used because it can better accommodate the construction of shaped structures such as variable sections.The complexity of the construction process makes the construction risk have certain randomness,so this paper proposes a cloudbased coupled matter-element model to address the ambiguity and randomness in the safety risk assessment of overturning construction of towering structures.In the pretended model,the digital eigenvalues of the cloud model are used to replace the eigenvalues in the matter–element basic element,and calculate the cloud correlation of the risk assessment metrics through the correlation algorithm of the cloud model to build the computational model.Meanwhile,the improved hierarchical analysis method based on the cloud model is used to determine the weight of the index.The comprehensive evaluation scores of the evaluation event are then obtained through the weighted average method,and the safety risk level is determined accordingly.Through empirical analysis,(1)the improved hierarchical analysis method based on the cloud model can incorporate the data of multiple decisionmakers into the calculation formula to determine theweights,which makes the assessment resultsmore credible;(2)the evaluation results of the cloud-basedmatter-element coupledmodelmethod are basically consistent with those of the other two commonly used methods,and the confidence factor is less than 0.05,indicating that the cloudbased physical element coupled model method is reasonable and practical for towering structure overturning;(3)the cloud-based coupled element model method,which confirms the reliability of risk level by performing Spearman correlation on comprehensive assessment scores,can provide more comprehensive information of instances compared with other methods,and more comprehensively reflects the fuzzy uncertainty relationship between assessment indexes,which makes the assessment results more realistic,scientific and reliable.

Study on Evaluation Method of Teaching Quality Based on Cloud Model and D-S Theory

The Evaluation of teaching quality is a complicated project. It’s a typical problem of uncertainty. A design scheme of teaching quality evaluation method based on cloud model and D-S theory is proposed with the school teaching evaluation index. With the experiences and knowledge of experts, evaluation index was described by cloud model and judgment matrix of AHP was revised by D-S theory. The weight of evaluation indexes was determined reasonably and objectively. Applied in the actual environment, the method can make an accurate and efficient evaluation with a certain practical value.

Parameterization and Explicit Modeling of Cloud Microphysics:Approaches, Challenges, and Future Directions

Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resolution limited-area models such as cloud-resolving models(CRMs)and large-eddy simulation(LES)models.Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years,this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations:multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions;discrete vs“continuous”representation of hydrometeor types;turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation;theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology;and approaches for developing bulk microphysics parameterizations.Also presented are the spectral bin scheme and particle-based scheme(especially,super-droplet method)for representing explicit microphysics.Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations.Particle-resolved direct numerical simulation(DNS)models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds.Outstanding challenges and future research directions are explored as well.

基于组合赋权-云模型的智能建造应用成熟度的评价

为解决传统施工方式存在的问题,建筑施工企业向智能建造方式逐渐转型已是大势所趋。针对新时代、新基建对智能建造施工的要求并结合能力成熟度理论,提出一种基于组合赋权-云模型的智能建造应用成熟度评价模型。首先,从施工、智能、其他3个维度,构建包含勘测、设计规划、施工现场管理、资源要素、智能建造技术、数据驱动、企业顶层设计7个类别的智能建造应用成熟度评价体系。其次,采用G1法与熵权法确定各指标的主、客观权重,运用博弈论进行权重组合。最后,通过云模型展示施工企业智能建造应用成熟度等级,并依据评价结果进行展望。研究结果表明:施工企业智能建造应用成熟度评价等级为“集成共享级”,评价结果与该企业实际情况吻合,验证了本文方法的适用性与科学性,为施工企业智能建造应用的发展提供科学依据。

基于博弈-可拓云的地铁-常规公交换乘服务评价

为了解决地铁与常规公交换乘服务评价方法的单一性和滞后性等问题,提出一种博弈-可拓云组合模型。结合“全、简、精、实”四类原则构建评价指标体系,分别利用层次分析法、CRITIC法、博弈论确定各项指标的主、客综合权重,并将数值代入可拓云模型实现二者的结合。以石家庄地铁为例,对辖区三条线路与常规公交间的换乘服务进行综合评价,结果显示:1、2、3号线的分数均处于[70,90)范围内,属于良好等级。评价结果与该市地铁-常规公交的运营现状相符,验证了组合模型的可行性与普适性,该结果对科学制定精准化的公共交通换乘服务政策提供参考。

工程机械品质鉴定模糊评价方法的研究

针对工程机械设备品质鉴定的模糊性、随机性和冲突性,提出基于云模型和证据理论的工程机械品质鉴定模糊评价方法。该方法的要点:根据设备功能结构特点及故障形式构建品质鉴定指标体系;对层次分析法中的专家评语、权重计算等做云模型处理;将云模型表示的专家评估意见用云模型相似度算法转化为基本概率分配,并用证据理论进行融合;基于最大信任准则确定设备品质等级。通过二手悬臂式掘进机品质鉴定展示该方法的实施过程,实例分析验证了该方法的有效性。

基于足迹理论的钢铁企业低碳选址评价方法

为推动钢铁企业在资源约束下完成产业升级,在环境约束下提升技术效率,提出一种基于足迹理论的钢铁企业低碳选址评价方法。首先,在钢铁企业常规选址指标的基础上,以足迹理论表征的环境支持力和压力指标为切入点,客观评估待选地区环境容量对新建厂址的容许程度,利用改进灰色关联度完成指标定量筛选,构建钢铁企业低碳选址评价体系。其次,运用差异系数法将主客观权重进行组合优化,采用可拓云模型求解选址综合评价等级隶属度和特征值,并结合可信度因子进行检验。最后,以某钢铁企业产能置换选址为例,确定待选厂址的评价等级。该方法在钢铁企业低碳选址综合评价中具有较好的可行性和适用性。

基于博弈组合赋权-云模型的坚硬顶板采场来压强度等级评估研究

为了解决坚硬顶板采场来压强度等级评估的不确定性问题,在力学分析的基础上,从顶板条件、地质条件、开采条件和其他条件等4个方面选取14个指标因素,采用序关系法确定主观权重、改进的CRITIC法确定客观权重,运用博弈论组合赋权,得到最佳综合权重,构建坚硬顶板采场来压强度等级评估云模型。通过云相似度测算,提高评估结果的精确性。以淮南张集矿区11129工作面为例,对9-2煤层上覆坚硬顶板来压强度等级进行评估,应用表明:所提方法综合考虑评价对象的主客观因素,权重分配科学合理,评估结果与实际情况一致,能为现场顶板弱化工作提供理论依据。

基于改进AHP及云模型的水轮机调节系统状态评价

针对水轮机调节系统综合评价不够全面,无法综合反映系统多指标、多层次的复杂性问题,提出了基于模糊层次分析法(AHP)-决策与实验室评估法(DEMATEL)-云模型的水轮机调节系统综合评价模型。首先建立基于主要设备和相关工况的多层次指标体系,采用模糊AHP计算评价指标的初始权重;通过DEMATEL法计算评价指标的相互影响与参照关系,绘制出指标因果关系图,并结合初始权重计算评价指标的综合权重;引入云模型得到评价指标各等级的隶属度矩阵。最后将权重结果与隶属度结合,得到系统综合评价等级。算例分析表明,该方法可高效快捷地对水轮机调节系统运行状态进行客观评价,为状态检修提供参考依据。

政协云与政协履职深度融合机制研究

政协云是政协委员政协履职的重要数字化平台。对23位具有代表性政协委员采用一对一访谈、小组座谈、头脑风暴等方式,了解其使用政协云进行履职的体验与感受、存在的问题与改进意见等。运用扎根理论对所得到的访谈内容进行整理和分析。在用户体验理论和信息生态理论视角下,构建了管理持续优化下的服务与保障相结合的政协云与政协履职融合机制,并给出了三点建议:以人性化管理保障委员全身心履职、以智慧化系统助力委员轻松履职、以贴心化服务助力委员便利履职。

基于可拓云理论的化工建筑施工安全风险评估

引入可拓云理论构建了化工建筑施工安全风险评估模型,在该模型内,最优最劣法和CRITIC法分别用于计算主客观权重值。研究应用博弈论确定组合赋权权重值,以消除主客观权重法之间的误差。最后,计算可拓云模型内模糊等级特征期望值Erq、模糊等级特征熵值Ers、综合评判向量B和置信度因子g等参数。结果表明:该化工项目施工安全综合风险等级为中等,模糊等级特征期望值Erq为2.952 8,模糊等级特征熵值Ers为0.016 5,置信度因子g为0.005 6,符合一致性要求,结果可信。研究结果为现场安全管理人员提供参考。

土石坝运行安全评价的改进组合赋权-云模型

针对土石坝运行安全评价中指标间相互影响、主客观权重赋值不够合理以及隶属区间模糊性等问题,提出了一种土石坝运行安全评价的改进组合赋权-云模型。以运行期土石坝为对象,构建了土石坝安全评价指标体系,分别采用G1法和改进熵权法对评价指标进行主客观赋权,融合博弈论思想求解最优权重组合系数,并引入云模型理论降低评价过程中隶属区间的模糊性。对某土石坝安全状态进行评价并与两种传统组合赋权法进行了对比,结果表明,3种评价方法的评价结果相近且与实际情况相符,但改进组合赋权-云模型考虑了评价指标间的关联性,运用博弈论思想使主客观权重赋值更加合理,能更客观地反映土石坝的真实运行状态。

基于博弈论组合赋权-云模型的消防员训练损伤风险评估

为降低消防员训练损伤发生率,从个人因素、环境因素和组织管理因素3个方面,提出包含19个指标的消防员训练损伤风险评估指标体系;采用Bonferroni有序加权平均算子(BON-OWA算子)修正层次分析法(AHP)的误差,获得各指标的主观权重;引用基于指标相关性的权重确定法(CRITIC)确定各指标的客观权重;基于博弈论组合赋权法确定各指标的组合权重;引入云模型理论,建立消防员训练损伤风险评估模型,并以河南省某消防救援大队消防员的训练为例,验证该模型的科学性。结果表明:训练装备的战技性能状况指标对消防员的训练损伤风险等级影响最大;该风险评估模型通过数据处理,可以确定消防员训练损伤风险等级;案例中,消防员在5种不同情景下的训练损伤风险等级均为一般风险,这与模糊综合评价法所得结果一致。

人工等离子体云团与无人机群的散射研究

电离层中释放的金属蒸气产生人工等离子体云团,其可显著改变无线电波传播。本文利用几何绕射理论(geometrical theory of diffraction, GTD)和有限元法(finite element method, FEM)相结合的方法,给出了经由天线、人工等离子云团和无人机(unmanned aerial vehicle, UAV)群组成的传播链路中信号强度计算方法。利用30~70 MHz甚高频(very high frequency, VHF)信号研究人工等离子体云团与UAV群的复合散射特性,得出如下结论:接收功率随着信号频率增加呈下降趋势;当机群由N架UAV构成时,阵因子迭加使机群雷达散射截面(radar cross section, RCS)出现一定的起伏,同相迭加时,接收功率可比单个UAV高约20lg N dB;利用人工等离子体云团散射可实现VHF频段用于对米级尺度RCS目标进行超视距探测,有助于解决紧急情况下电离层扰动对高频探测的不利影响。

面向森林火灾的人工巡视与无人机巡视效益评估

为建立森林火灾人工巡视与无人机巡视效益评估框架,推动人工巡视和无人机巡视的综合运用。提出结合人工和无人机巡视影响因素,建立包括4个一级指标、8个二级指标和18个三级指标的巡视效益评估指标体系,通过博弈论组合赋权法确定各指标权重的最优组合权重,运用云模型分别构建出无人机和人工巡视技术效益评估模型。研究结果表明:人工巡视和无人机巡视的效益评估指标体系的一级指标相同,而二级指标不同之处在于物资保障和航行稳定性;将该巡视效益评估模型应用于祁连山森林,验证评估模型的客观性与全面性。研究结果可为人工和无人机森林火灾巡视效益评估提供有效工具。

基于证据推理的隧道坍塌多源信息融合评估

由于影响因素众多,隧道坍塌风险评估是一个多属性决策问题.单源信息评估方法难以充分考虑所有的风险因素,导致预测结果存在偏差.为了评估隧道坍塌风险并提供更准确的风险控制策略,本研究提出了一种新的多源信息融合方法,该方法将云模型(CM)、支持向量机(SVM)和基于证据推理(ER)相结合.对多个信息源进行分析,得到不同的坍塌风险评估模型(目视检查数据通过SVM获取分类概率值,监测数据通过云模型获取概率值).每个模型的质量都由可信度和重要性权重来评价.然后运用ER规则融合各个评估模型的结果,给出总体的坍塌概率风险评估.与D-S理论相比,ER规则在处理高冲突信息方面具有更大的优势.当不同信息源的风险评估结果不一致时,D-S理论的融合结果往往会与常识相反,ER规则融合由于考虑了评估模型的重要性权重和可信度,更适用于高冲突信息的融合.该方法已成功应用于福建莆炎高速公路的鱼塘溪隧道.结果表明,所提出的多源信息融合方法的评价准确率为87.5%,而单源信息融合方法的评价准确率小于70%.此外,即使不同模型的风险结果存在较大的冲突,该融合模型也具有良好的性能.