Evaluation of toppling rock slopes using a composite cloud model with DEMATEL–CRITIC method

Safety evaluation of toppling rock slopes developing in reservoir areas is crucial. To reduce the uncertainty of safety evaluation, this study developed a composite cloud model, which improved the combination weights of the decision-making trial and evaluation laboratory (DEMATEL) and criteria importance through intercriteria correlation (CRITIC) methods. A safety evaluation system was developed according to in situ monitoring data. The backward cloud generator was used to calculate the numerical characteristics of a cloud model of quantitative indices, and different virtual clouds were used to synthesize some clouds into a generalized one. The synthesized numerical characteristics were calculated to comprehensively evaluate the safety of toppling rock slopes. A case study of a toppling rock slope near the Huangdeng Hydropower Station in China was conducted using monitoring data collected since operation of the hydropower project began. The results indicated that the toppling rock slope was moderately safe with a low safety margin. The composite cloud model considers the fuzziness and randomness of safety evaluation and enables interchange between qualitative and quantitative knowledge. This study provides a new theoretical method for evaluating the safety of toppling rock slopes. It can aid in the predication, control, and even prevention of disasters.

Comprehensive evaluation of 5G+smart distribution network based on combined weighting method-cloud model

With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.

Mining Weights of Land Evaluation Factors Based on Cloud Model and Correlation Analysis

The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.

Model of Security Evaluation of Infrastructure as a Service Layer of Cloud Computing System

At present,most providers of cloud computing mainly provide infrastructures and services of infrastructure as a service(IaaS).But there is a serious problem that is the lack of security standards and evaluation model of IaaS.After analyzing the vulnerabilities performance of IaaS cloud computing system,the mapping relationship was established between the vulnerabilities of IaaS and the nine threats of cloud computing which was released by cloud security alliance(CSA).According to the mapping relationship,a model for evaluating security of IaaS was proposed which verified the effectiveness of the model on OpenStack by the analytic hierarchy process(AHP) and the fuzzy evaluation method.

Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies(GISS) Model E2 atmospheric general circulation model(GCM; post-CMIP5,hereafter P5). In this study, single column model(SCM P5) simulated cloud fractions(CFs), cloud liquid water paths(LWPs)and precipitation were compared with Atmospheric Radiation Measurement(ARM) Southern Great Plains(SGP) groundbased observations made during the period 2002–08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase(10%–20%) but precipitation increased significantly(56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

Risk transmission evaluation for parallel construction of warships based on IFCM and the cloud model

To cope with multi-directional transmission coupling,spreading, amplification, and chain reaction of risks during multiproject parallel construction of warships, a risk transmission evaluation method is proposed, which integrates an intuitionistic cloud model with a fuzzy cognitive map. By virtue of expectancy Ex, entropy En, and hyper entropy He, the risk fuzziness and randomness of the knowledge of experts are organically combined to develop a method for converting bi-linguistic variable decision-making information into the quantitative information of the intuitionistic normal cloud(INC) model. Subsequently, the threshold function and weighted summation operation in the traditional fuzzy cognitive map is converted into the INC ordered weighted averaging operator to create the risk transmission model based on the intuitionistic fuzzy cognitive map(IFCM) and the algorithm for solving it. Subsequently, the risk influence sequencing method based on INC and the risk rating method based on nearness are proposed on the basis of Monte Carlo simulation in order to realize the mutual conversion of the qualitative and quantitative information in the risk evaluation results.Example analysis is presented to verify the effectiveness and practicality of the methods.

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.

Evaluation and Forecasting of Wind Energy Investment Risk along the Belt and Road Based on a Novel Hybrid Intelligent Model

The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road.In order to obtain the scientific and real-time forecasting result,this paper constructs a novel hybrid intelligent model based on improved cloud model combined with GRA-TOPSIS and MBA-WLSSVM.Firstly,the factors influencing investment risk of wind energy along the Belt and Road are identified fromthree dimensions:endogenous risk,exogenous risk and process risk.Through the fuzzy threshold method,the final input index system is selected.Secondly,the risk evaluation method based on improved cloud model andGRA-TOPSIS is proposed.Thirdly,a modern intelligent model based on MBA-WLSSVMis designed.In modified bat algorithm(MBA),tent chaotic map is utilized to improve the basic bat algorithm,while weighted least squares support vector machine(WLSSVM)adopts wavelet kernel function to replace the traditional radial basis function to complete the model improvement.Finally,an example is given to verify the scientificity and accuracy of themodel,which is helpful for investors tomake fast and effective investment risk forecasting of wind energy along the Belt and Road.The example analysis proves that the proposedmodel can provide reference and basis for investment corpus to formulate the investment strategy in wind energy along the Belt and Road.

基于Cloud Model的大学生毕业质量评分模型的研究

毕业生质量的评价模型应该是动态的、分层次的、多属性的,这样才能给高校教学工作者和管理层提供更加全面和及时的反馈信息,从而更好的推动高等学校人才的培养。本文在已有的评测模型的基础上,引入相对全面的评价指标体系,对测试过程进行系统开发,最后以某届毕业生的评测过程为例,以验证评价模型和系统的正确性、稳定性。

Quantitative credibility evaluation of Global Energy Interconnection data

The development of Global Energy Interconnection(GEI)is essential for supporting a wide range of basic data resources.The Global Energy Interconnection Development and Cooperation Organization has established a comprehensive data center covering six major systems.However,methods for accurately describing and scientifically evaluating the credibility of the massive amount of GEI data remain underdeveloped.To address this lack of such methods,a GEI data credibility quantitative evaluation model is proposed here.An evaluation indicator system is established to evaluate data credibility from multiple perspectives and ensure the comprehensiveness and impartiality of evaluation results.The Cloud Model abandons the hard division of comments to ensure objectivity and accuracy in evaluation results.To evaluate the suitability of the proposed method,a case analysis is conducted,wherein the proposed method demonstrates sufficient validity and feasibility.

User’s Relevance of PIR System Based on Cloud Models

A new method to evaluate fuzzily user’s relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval (PIR) system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.

Mathematical Modeling of the Influence of the Wind Field Structure in the Atmosphere on the Cloud Formation Processes

The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.

3D geological suitability evaluation for underground space based on the AHP-cloud model

Urban development continues to reduce the amount of available ground space.The development of underground space is thus gath-ering increasing attention to alleviate ground congestion.However,there is currently a lack of a three-dimensional(3D)evaluation method to systematically evaluate the geological conditions of underground space and possible geological disaster risks caused by rock and soil masses.This paper presents an engineering geological suitability assessment framework based on 3D geological modeling and an analytic hierarchy process(AHP)-cloud model.As the basis for 3D evaluation,a 3D structural model of the study area is established based on the drilling data and geological profiles.Then the structural model is partitioned to obtain interpolation grids,and the ordinary Kriging interpolation method is applied to attribute interpolation.All the attributes are exported from the geological model,and the rock and soil masses are divided into four categories according to their engineering properties,namely soft soil,sandy soil,cohesive soil,and rock,upon which a targeted hierarchy structure is established based on the attributes that impact the suitability.This paper intro-duces the cloud model to characterize the uncertainty of these evaluation indexes,which synthesizes an AHP method,thus it is referred to as the AHP-cloud model.This new model is used to evaluate the geological suitability of underground space in the Sanlong Bay district,Foshan City,Guangdong,China.In addition,we also determine the excavation difficulty at different depths according to the lithology and weathering degree of the study area.The limitations and future directions of the proposed method are discussed,including the influ-encing factors and weight determination.

基于组合赋权-云模型的城市洪涝灾害韧性评价方法

基于城市系统应对洪涝灾害事件的响应过程,从基础抵御、防灾预警、应急响应和适应恢复4个方面构建了包含4个一级指标和20个二级指标的城市洪涝灾害韧性评价指标体系,在此基础上通过可拓层次分析法和熵权法对指标分别进行主观和客观赋权,结合博弈论理论进行组合赋权,提出了基于组合赋权-云模型的城市洪涝灾害韧性评价方法。南京市6个行政区的验证结果表明:该方法可有效评价城市洪涝灾害韧性水平,6个行政区中建邺区、江宁区为高韧性地区,鼓楼区、秦淮区为较高韧性地区,雨花台区为中等韧性地区,溧水区为较低韧性地区。

基于TFN-AHP和云模型的母舰对气垫船保障能力评价

母舰对气垫船的保障能力是气垫船任务执行能力的重要组成部分,对母舰的保障能力进行综合评价是提升气垫船与母舰保障适配能力的重要环节。母舰对气垫船的保障活动具有高度的随机性、复杂性和动态性,导致其保障能力的评价也存在不确定性和模糊性。为此,基于三角模糊数(triangular fuzzy number,TFN)-层次分析法(analytic hierarchy process,AHP)与云模型提出了一种新的母舰对气垫船保障能力评价方法,并对某型母舰对气垫船的保障能力进行了评价。该方法通过特定的结构算法完成定性概念与定量表示的相互结合,降低了保障能力评价中权重计算的主观性和随机性,为母舰对气垫船保障能力评价提供了借鉴。

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。

基于组合赋权三维云评估技术的深部煤矿顶板事故风险分析

为了更好地对深部煤矿顶板事故展开风险评价,提出了组合赋权三维云评估技术。基于事故统计及事故致因理论,对深部煤矿顶板事故风险指标体系展开研究,采用博弈论对改进层次分析法(Analytic Hierarchy Process,AHP)和熵权法进行博弈分析,以实现风险指标的组合赋权,通过构建三维云模型,对深部煤矿顶板事故危险性进行可视化分析。结果表明:包括行为、技术、设备、环境、管理5大风险因素在内的一级指标并其下20个二级风险指标是深部煤矿顶板事故风险评价指标体系的主体内容,且以环境风险权重最大;由三维云评估技术分析可知,平煤九矿的顶板事故风险级别为Ⅲ级,即修复后可接受,与该矿生产实际情况相符。组合赋权三维云评估技术的提出有助于完善深部煤矿顶板事故风险评价方法,可应用于工程实践。

基于C-OWA和云模型的高校化工实验室安全韧性评价

为了探索高校化工实验室安全管理的新范式,将安全韧性理论引入高校化工实验室安全研究中,提出一种安全韧性评价方法。首先,界定高校化工实验室安全韧性的概念,构建以稳定性、冗余性、效率性和适应性4个安全韧性特征要素为核心的评价指标体系;其次,基于有序加权平均C-OWA算子计算指标权重,通过云模型理论得到各安全韧性特征要素和安全韧性的评价等级。最后,将该方法应用于武汉市某高校化学与化工学院实验楼安全评价,结果表明:该实验楼的实验室稳定性等级为“较好(Ⅳ级)”,冗余性等级为“中等(Ⅲ级)”,效率性等级为“较好(Ⅳ级)”,适应性等级为“中等(Ⅲ级)”,整体安全韧性等级为“较好(Ⅳ级)”,评价结果与实际情况相符,运用该方法进行安全评价对改善高校化工实验室的安全状态具有一定的参考意义。

基于云-TOPSIS-灰关联分析模型的产品服务系统方案评价技术

方案评价是产品服务系统设计的关键环节之一,评价结果的合理性对企业发展至关重要。基于最小平方和法,构建了云-TOPSIS-灰关联分析模型,对产品服务系统方案进行评价。引入云模型和相对偏好关系量化离散型指标,解决专家评价的模糊性和随机性问题。运用TOPSIS灰关联分析法确定正、负理想灰关联系数矩阵,集成指标权重和正、负理想灰关联系数矩阵建立正、负理想加权灰关联系数矩阵,兼顾了几何方案序列曲线的位置接近度和形状相似度。运用最小平方和法求解灰关联投影系数,确定方案排序。以某农业装备企业拖拉机产品服务系统方案评价为实例,验证了所提模型的科学性和可行性。

基于云-TOPSIS法的应急物流供应商综合评价

为实现应急物流降本增效的目标,从供应商层面出发,运用云-逼近理想解排序法(TOPSIS)评价应急物流供应商综合能力;根据应急物流特点,从应急响应能力、物资质量、成本控制、应急响应柔性、企业内外部条件等5方面,构建应急物流供应商综合评价指标体系;借鉴博弈论思想,将用改进熵权法求得的客观权重和用层次分析法(AHP)求得的主观权重作为博弈对手,确定最优组合权重;运用云模型量化指标决策云和加权云对供应商的模糊定性评价语义;采用TOPSIS法构建正负理想解集合,计算备选方案与正负理想解的距离确定相对贴近度,确定最优备选方案。研究结果表明:指标决策云能准确地将评价语言量化,云-TOPSIS法的评价结果更合理;在供应商相对贴近度排序中,采用云-TOPSIS法计算的最优与最劣者差值为0.3315,而TOPSIS法为0.0882,两者相差0.2433,表明云-TOPSIS法的评价结果区分度更大,能更直观地辅助决策者做出最优选择。