Self-Organized Criticality Theory Model of Thermal Sandpile

A self-organized criticality model of a thermal sandpile is formulated for the first time to simulate the dynamic process with interaction between avalanche events on the fast time scale and diffusive transports on the slow time scale. The main characteristics of the model are that both particle and energy avalanches of sand grains are considered simultaneously. Properties of intermittent transport and improved confinement are analyzed in detail. The results imply that the intermittent phenomenon such as blobs in the low confinement mode as well as edge localized modes in the high confinement mode observed in tokamak experiments are not only determined by the edge plasma physics, but also affected by the core plasma dynamics.

Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

generalizedBarabasi 艾伯特(GBA ) 上的自我组织的 criticality 的一个修改进化模型没有规模的网络被调查。在我们的模型，我们发现空间、时间的关联展出批评行为。更重要地，这些批评行为随着参数 b 变化，哪个重量与在 GBA 网络进化的度比较的距离。

Self-organized Criticality in an Earthquake Model on Random Network

一个随机的网络上的一个简化 Olami-Feder-Christensen 模型被学习了。我们建议一条新倒下规则—当有一个不稳定的地点，倒下时，这个地点的精力不平均随机被再分配到它的最近的邻居。当系统是保守人士，和系统的分发服从有限尺寸可伸缩的雪崩尺寸概率时，模拟结果显示模型显示自我组织的 criticality。什么时候系统 isnonconservative，模型不显示可伸缩行为。我们有不同最近的邻居 q 的模型的模拟结果 aiso 被比较，它显示空间拓扑学不改变系统的批评行为。

The Research of Transmission Network Planning Based on System’s Self-organized Criticality

This paper presents a new line importance degree evaluation index for the propagation of cascading failures, which is used to quantify transmission lines for cascade spread. And propose an improved capital matching model, according to the results of the evaluation, to enhanced robustness of the power system. The simulation results proved that in the case of the same system, the new model can inhibit cascade spread, reduce the probability of large-scale blackouts.

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.

基于CRITIC-TOPSIS模型的图书馆图书供应商评价研究

[目的/意义]旨在构建图书供应商的评价指标体系与评价模型,为图书馆优选图书供应商提供决策依据和方法。[方法/过程]以BSC模型为分析基础从供应商的影响力、供应能力、服务水平、价格、响应能力等维度形成了图书供应商的评价指标体系,构建了CRITIC-TOPSIS评价模型,以对图书供应商进行评价和选择。[结果/结论]该评价模型考虑了评价指标间的变异性和相关性,缓解了选择图书供应商时存在的主观不确定性,可以为图书馆选择优质图书供应商提供方法和指导。

Deformation critical threshold estimation of Xiaowan ultrahigh arch dam with time-varying grey model

The structural behavior of the Xiaowan ultrahigh arch dam is primarily influenced by external loads and time-varying characteristics of dam concrete and foundation rock mass during long-term operation. According to overload testing with a geological model and the measured time series of installed perpendicular lines, the space and time evolution characteristics of the arch dam structure were analyzed, and its mechanical performance was evaluated. Subsequently, the deformation centroid of the deflective curve was suggested to indicate the magnitude and unique distribution rules for a typical dam section using the measured deformation values at multi-monitoring points. The ellipse equations of the critical ellipsoid for the centroid were derived from the historical measured time series. Hydrostatic and seasonal components were extracted from the measured deformation values with a traditional statistical model, and residuals were adopted as a grey component. A time-varying grey model was developed to accurately predict the evolution of the deformation behavior of the ultrahigh arch dam during future operation. In the developed model, constant coefficients were modified so as to be time-dependent functions, and the prediction accuracy was significantly improved through introduction of a forgetting factor. Finally, the critical threshold was estimated, and predicted ellipsoids were derived for the Xiaowan arch dam. The findings of this study can provide technical support for safety evaluation of the actual operation of ultrahigh arch dams and help to provide early warning of abnormal changes.

Dimensionality Reduction Using Optimized Self-Organized Map Technique for Hyperspectral Image Classification

The high dimensionalhyperspectral image classification is a challenging task due to the spectral feature vectors.The high correlation between these features and the noises greatly affects the classification performances.To overcome this,dimensionality reduction techniques are widely used.Traditional image processing applications recently propose numerous deep learning models.However,in hyperspectral image classification,the features of deep learning models are less explored.Thus,for efficient hyperspectral image classification,a depth-wise convolutional neural network is presented in this research work.To handle the dimensionality issue in the classification process,an optimized self-organized map model is employed using a water strider optimization algorithm.The network parameters of the self-organized map are optimized by the water strider optimization which reduces the dimensionality issues and enhances the classification performances.Standard datasets such as Indian Pines and the University of Pavia(UP)are considered for experimental analysis.Existing dimensionality reduction methods like Enhanced Hybrid-Graph Discriminant Learning(EHGDL),local geometric structure Fisher analysis(LGSFA),Discriminant Hyper-Laplacian projection(DHLP),Group-based tensor model(GBTM),and Lower rank tensor approximation(LRTA)methods are compared with proposed optimized SOM model.Results confirm the superior performance of the proposed model of 98.22%accuracy for the Indian pines dataset and 98.21%accuracy for the University of Pavia dataset over the existing maximum likelihood classifier,and Support vector machine(SVM).

Research on percolation model and criticality of seismicity

Making use of modern nonlinear physics theory and earthquake focus theory, combined with seismicity characteristics, the percolation model of earthquake activity is given in this paper. We take the seismogenic process of alarge earthquake as a phase transition process of percolation and apply the renormalization method to phase transition of percolation. The critical property of the system, which is like percolation probability exponential andcorrelative length exponential, etc, can be calculated under the fixed point as which in the renormalization transformation infinite correlative length in percolation phase transition is taken. The percolation phase transition process of two large earthquakes, which are Haicheng and Tangshan event occurred in 1975 and 1976 respectively, hasbeen discussed by means of seismicity data before and after two shocks.

Numerical analysis of high‑speed railway slab tracks using calibrated and validated 3D time‑domain modelling

Concrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks,provide safe and smooth rides,and reduce the maintenance frequency.In this paper,the elastic performance of a novel slab trackform for high-speed railways is investigated using three-dimensional finite element modelling in Abaqus.It is then compared to the performance of a ballasted track.First,slab and ballasted track models are developed to replicate the full-scale testing of track sections.Once the models are calibrated with the experimental results,the novel slab model is developed and compared against the calibrated slab track results.The slab and ballasted track models are then extended to create linear dynamic models,considering the track geodynamics,and simulating train passages at various speeds,for which the Ledsgard documented case was used to validate the models.Trains travelling at low and high speeds are analysed to investigate the track deflections and the wave propagation in the soil,considering the issues associated with critical speeds.Various train loading methods are discussed,and the most practical approach is retained and described.Moreover,correlations are made between the geotechnical parameters of modern high-speed rail and conventional standards.It is found that considering the same ground condition,the slab track deflections are considerably smaller than those of the ballasted track at high speeds,while they show similar behaviour at low speeds.

Electrical Tree Simulation Based on the Self-Organization Criticality

So far much effort has been made to understand the development of electrical treeing. For the simulation based study of electrical treeing, the most common method is to apply DBM stochastic model to simulate the growing of electrical treeing patterns. Previous simulation results showed that this stochastic model is capable of simulating the real electrical treeing patterns in a point-to-plane electrode system. However, this model only allows the tree channels to propagate on equipotential lines proportional to local electrical field. Therefore, it is necessary to develop a novel stochastic model to simulate the electrical patterns in order to get a good agreement with experimental results.

On the Teaching Design of Graduates’EAP Course:Enhancing Language Proficiency and Critical Thinking Skills

This paper explores the integration of the bridge-in,objectives,pre-assessment,participatory activities,post-assessment and summary(BOPPPS)teaching model within the context of the post-graduates Academic English course.It discusses how this structured approach can effectively enhance students’language proficiency,foster critical thinking skills,and align with the multifaceted objectives of advanced English language education.The study provides a detailed examination of each BOPPPS component as applied to the post-graduates Academic English curriculum,supported by theoretical underpinnings and practical implications.

基于云模型和DEMATEL-CRITIC的起重机金属结构安全评估

文中针对起重机金属结构安全评估过程中存有模糊性与随机性的问题,提出了基于云模型和DEMATEL-CRITIC的分级安全评估方法。以云模型相关理论为基础,利用正态云模型得出各评估指标于不同安全评估等级的隶属度,以实现模糊概念的随机表示。采用DEMATEL和改进的CRITIC方法生成可信度更高且兼顾主客观的综合权重,计算得出各评估结构综合隶属度,进而确定整机金属结构的安全等级,综合评价了起重机的安全状态。通过案例分析验证了该方法的准确性和有效性,为起重机金属结构安全评估提供新方法。

基于CRITIC-TOPSIS的配电站房运行状态评估

实现配电站房运行状态的准确评估对确保电力系统的稳定运行有着重要的意义。针对目前评估方法主观性过强的问题,提出了一种基于CRITIC-TOPSIS的配电站房运行状态评估方法。基于压力-状态-响应(PSR)框架的思维模式,建立科学合理的配电站房运行状态评估指标体系,采用CRITIC赋权法确定各评价指标的权重,减少评价过程中的主观性,建立CRITIC-TOPSIS评价模型,利用综合接近度评估配电站房相对运行状态,并确定状态等级;引入禀赋效应来根据决策者的心理行为对评价结果进行调整,并对配电站房状态情况进行优劣排序;根据某地区配电站房实际运行数据进行实例分析,所得评价结果具有客观性和合理性。

基于CRITIC和云模型的航天标准化师评价方法研究

针对目前航天标准化师评价方法存在的问题,建立了基于CRITIC和云模型的评价模型。首先,采用文献成熟的评价指标构建了航天标准化师评价指标体系;其次,用CRITIC法对专家评分进行处理,并确定了评价指标的权重;然后,建立了云模型评价方法对航天标准化师进行评价;最后,对模型进行了实例分析。结果表明:该模型是一种合理科学的评价优选模型,能够针对航天标准化师的评价工作取得合理和有效的结果。

Criticality in Two-Variable Earthquake Model on a Random Graph

A two-variable earthquake model on a quenched random graph is established here.It can be seen as a generalization of the OFC models.We numerically study the critical behavior of the model when the system is nonconservative:the result indicates that the model exhibits self-organized criticality deep within the nonconservative regime.The probability distribution for avalanche size obeys finite size scaling.We compare our model with the model introduced by Stefano Lise and Maya Paczuski [Phys.Rev.Lett.88 (2002) 228301],it is proved that they are not in the same universality class.

G1-CRITIC组合赋权云模型下的储能电站火灾风险评价

锂离子电池储能电站火灾事故频繁发生且损失严重,对锂离子电池储能电站火灾风险开展研究可有效预防火灾的发生。首先根据物理-事理-人理(WSR)理论,构建锂电池特性、消防设施、安全管理和人员因素4个一级指标、12个二级指标和32个三级指标的锂离子电池储能电站火灾风险评价指标体系;然后运用序关系分析(G1)法确定各评价指标的主观权重,采用CRITIC法(Criteria Importance Though Intercriteria Correlation,CRITIC)确定客观权重,基于拉格朗日乘法优化后的最小信息熵原理确定组合权重,并结合云模型理论建立锂离子电池储能电站火灾风险评价模型。以某磷酸铁锂储能电站为例开展火灾风险等级评价,结果表明:储能电站火灾风险综合云特征值为(71.3104,1.2142,0.2568),火灾风险等级处于“中风险”,在运行环境和防火设计等方面存在较严重的问题并亟需改进。评价结果与实际火灾风险等级相符,实例证明锂离子电池储能电站火灾风险评价模型能够较准确地反映储能电站火灾风险情况,为锂离子电池储能电站火灾预防与风险管控提供参考。

基于动态CRITIC赋权的中国金融压力指数构建与金融风险识别

合理测度和准确识别金融市场风险,对于稳定经济、有效防范金融风险意义重大。依据中国金融市场特征,本文采用动态CRITIC法计算权重并建立金融压力指数测度模型,通过非参数统计核密度法和B-N数据分解法对金融压力指数的分布和金融风险状态进行估计与识别,采用马尔科夫区制转换模型检验高低风险转换概率,并与基于确定项进行识别的结果进行对比分析。研究表明:基于动态CRITIC赋权的金融压力指数更能反映金融市场的极端值和金融风险,随机冲击是影响我国金融压力指数的重要因素,两种金融风险识别方法均可识别金融风险状态且各有优势,研究中可以互为补充。今后应建立更加完善的风险测度指标体系,进一步完善监管制度,加强对金融风险的宏观审慎管理和防范。

改进CRITIC与TOPSIS的区域建筑安全评价算法

为了监控区域建筑危险源,提高区域建筑的安全性水平,本文设计了一种区域建筑安全等级评价算法。该算法结合改进的CRITIC权重与TOPSIS模型,突出多个评价指标之间的比较强度,关注指标间的相互关系,充分考虑候选方案的全局最优解,对区域建筑安全等级的评价提出了具体的方法步骤。通过工程实例验证,本文算法在区域建筑安全等级评价中表现出明显优势,可以为决策者提供更科学、更合理的决策依据。

Critical behaviours and magnetic properties of three-dimensional bond and anisotropy dilution Blume-Capel model in the presence of an applied field

This paper studies the critical behaviours and magnetic properties of three-dimensional bond and anisotropy dilution Blume-Capel model （BCM） in the presence of an applied field within the effective field theory. The trajectory of tricritical point, reentrant transitions and degenerate patterns of anisotropy are obtained both for the bond and the anisotropy dilutions. The global phase diagrams demonstrate unusually reentrant phenomena. The temperature dependences of magnetization curves undergo remarkable spin glass behaviour at low temperatures, and transform from ferromagnetism to paramagnetism at high temperature in applied fields. Temperature dependence of magnetic susceptibility curve is in qualitative agreement with experimental result.