A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

Multimodal Social Media Fake News Detection Based on Similarity Inference and Adversarial Networks

As social networks become increasingly complex, contemporary fake news often includes textual descriptionsof events accompanied by corresponding images or videos. Fake news in multiple modalities is more likely tocreate a misleading perception among users. While early research primarily focused on text-based features forfake news detection mechanisms, there has been relatively limited exploration of learning shared representationsin multimodal (text and visual) contexts. To address these limitations, this paper introduces a multimodal modelfor detecting fake news, which relies on similarity reasoning and adversarial networks. The model employsBidirectional Encoder Representation from Transformers (BERT) and Text Convolutional Neural Network (Text-CNN) for extracting textual features while utilizing the pre-trained Visual Geometry Group 19-layer (VGG-19) toextract visual features. Subsequently, the model establishes similarity representations between the textual featuresextracted by Text-CNN and visual features through similarity learning and reasoning. Finally, these features arefused to enhance the accuracy of fake news detection, and adversarial networks have been employed to investigatethe relationship between fake news and events. This paper validates the proposed model using publicly availablemultimodal datasets from Weibo and Twitter. Experimental results demonstrate that our proposed approachachieves superior performance on Twitter, with an accuracy of 86%, surpassing traditional unimodalmodalmodelsand existing multimodal models. In contrast, the overall better performance of our model on the Weibo datasetsurpasses the benchmark models across multiple metrics. The application of similarity reasoning and adversarialnetworks in multimodal fake news detection significantly enhances detection effectiveness in this paper. However,current research is limited to the fusion of only text and image modalities. Future research directions should aimto further integrate features fromadditionalmodalities to comprehensively represent themultifaceted informationof fake news.

Research on the Renovation of Traditional Villages Based on Postmodernism

Traditional village as a part of cultural heritage shows unique historical,cultural and architectural characteristics.With the accelerating urbanization,ecological environment of traditional villages has been threatened,local cultures have degraded,even all traditional villages have shown similar images,thus effective protection and update is urgently needed.Based on the background and characteristics of postmodernist design,this study explored problems in the renovation of traditional villages,analyzed the renovation cases of some traditional villages and then concluded the scientific renovation strategies,so as to provide references for the future renovation design of traditional villages.

A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity matching.In the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and symmetry.Some com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

Structural similarity of lithospheric velocity models of Chinese mainland

Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.

Investigation on mechanical properties regulation of rock-like specimens based on 3D printing and similarity quantification

3D printing is widely adopted to quickly produce rock mass models with complex structures in batches,improving the consistency and repeatability of physical modeling.It is necessary to regulate the mechanical properties of 3D-printed specimens to make them proportionally similar to natural rocks.This study investigates mechanical properties of 3D-printed rock analogues prepared by furan resin-bonded silica sand particles.The mechanical property regulation of 3D-printed specimens is realized through quantifying its similarity to sandstone,so that analogous deformation characteristics and failure mode are acquired.Considering similarity conversion,uniaxial compressive strength,cohesion and stress–strain relationship curve of 3D-printed specimen are similar to those of sandstone.In the study ranges,the strength of 3D-printed specimen is positively correlated with the additive content,negatively correlated with the sand particle size,and first increases then decreases with the increase of curing temperature.The regulation scheme with optimal similarity quantification index,that is the sand type of 70/140,additive content of 2.5‰and curing temperature of 81.6℃,is determined for preparing 3D-printed sandstone analogues and models.The effectiveness of mechanical property regulation is proved through uniaxial compression contrast tests.This study provides a reference for preparing rock-like specimens and engineering models using 3D printing technology.

Similarity Criterion and Scale Effect for Ship Distortion Model Under Combined Loads

For the ultimate strength model test evaluation of large ship structures, the distortion model with non-uniform ratio between the main size and the plate thickness size is usually adopted. It is the key to carry out scale model test to establish a distortion model similar to the real ship structure under combined load. A similarity criterion for ship distortion model under the combined action of bending moment and surface pressure was proposed, and the scale effect for the criterion was verified by a se ries of numerical analysis and model tests. The results show that the similarity criterion for ship distor tion model under combined loads has a certain scale effect. For the model tests of ship cabin struc tures, it is suggested that the scale range between the plate thickness scale and the main dimension scale should be controlled within 2:1, which can be used as a reference for distortion model design and ultimate strength test of large-scale ship structures.

Numerical Simulation of the Settling Flux of Biodeposition in a Bay with Cage Culture Through Similarity Theory and a Simplified Pollution Source

The settling flux of biodeposition affects the environmental quality of cage culture areas and determines their environmental carrying capacity.Simple and effective simulation of the settling flux of biodeposition is extremely important for determining the spatial distribution of biodeposition.Theoretically,biodeposition in cage culture areas without specific emission rules can be simplified as point source pollution.Fluent is a fluid simulation software that can simulate the dispersion of particulate matter simply and efficiently.Based on the simplification of pollution sources and bays,the settling flux of biodeposition can be easily and effectively simulated by Fluent fluid software.In the present work,the feasibility of this method was evaluated by simulation of the settling flux of biodeposition in Maniao Bay,Hainan Province,China,and 20 sampling sites were selected for determining the settling fluxes.At sampling sites P1,P2,P3,P4,P5,Z1,Z2,Z3,Z4,A1,A2,A3,A4,B1,B2,C1,C2,C3 and C4,the measured settling fluxes of biodeposition were 26.02,15.78,10.77,58.16,6.57,72.17,12.37,12.11,106.64,150.96,22.59,11.41,18.03,7.90,19.23,7.06,11.84,5.19 and 2.57 g d^(−1)m^(−2),respectively.The simulated settling fluxes of biodeposition at the corresponding sites were 16.03,23.98,8.87,46.90,4.52,104.77,16.03,8.35,180.83,213.06,39.10,17.47,20.98,9.78,23.25,7.84,15.90,6.06 and 1.65 g d^(−1)m^(−2),respectively.There was a positive correlation between the simulated settling fluxes and measured ones(R=0.94,P=2.22×10^(−9)<0.05),which implies that the spatial differentiation of biodeposition flux was well simulated.Moreover,the posterior difference ratio of the simulation was 0.38,and the small error probability was 0.94,which means that the simulated results reached an acceptable level from the perspective of relative error.Thus,if nonpoint source pollution is simplified to point source pollution and open waters are simplified based on similarity theory,the setting flux of biodeposition in the open waters can be simply and effectively simulated by the fluid simulation software Fluent.

Similarity evaluation model for the internal defect detection of strip steel

An internal defect meter is an instrument to detect the internal inclusion defects of cold-rolled strip steel.The detection accuracy of the equipment can be evaluated based on the similarity of the multiple detection data obtained for the same steel coil.Based on the cosine similarity model and eigenvalue matrix model,a comprehensive evaluation method to calculate the weighted average of similarity is proposed.Results show that the new method is consistent with and can even replace artificial evaluation to realize the automatic evaluation of strip defect detection results.

Comparative Analysis of Energy Characteristics of Two Southwest Vortices in Sichuan Under Similar Circulation Backgrounds

Based on ERA5 reanalysis data,the present study analyzed the thermal energy development mechanism and kinetic energy conversion characteristics of two extreme rainstorm processes in relation to the shallow southwest vortex in the warm-sector during a“rain-generated vortex”process and the deep southwest vortex in a“vortex-generated rain”process.The findings were as follows:(1)During the extreme rainstorm on August 11,2020(hereinafter referred to as the“8·11”process),intense surface heating and a high-energy unstable environment were observed.The mesoscale convergence system triggered convection to produce heavy rainfall,and the release of latent condensation heat generated by the rainfall promoted the formation of a southwest vortex.The significant increase(decrease)in atmospheric diabatic heating and kinetic energy preceded the increase(decrease)in vorticity.By contrast,the extreme rainstorm on August 16,2020(hereinafter referred to as the“8·16”process)involved the generation of southwest vortex in a low-energy and highhumidity environment.The dynamic uplift of the southwest vortex triggered rainfall,and the release of condensation latent heat from rainfall further strengthened the development of the southwest vortex.The significant increase(decrease)in atmospheric diabatic heating and kinetic energy exhibited a delayed progression compared to the increase(decrease)in vorticity.(2)The heating effect around the southwest vortex region was non-uniform,and the heating intensity varied in different stages.In the“8·11”process,the heating effect was the strongest in the initial stage,but weakened during the vortex's development.On the contrary,the heating effect was initially weak in the“8·16”process,and intensified during the development stage.(3)The available potential energy of the“8·11”process significantly increased in kinetic energy converted from rotational and divergent winds through baroclinic action,and the divergent wind energy continued to convert into rotational wind energy.By contrast,the“8·16”process involved the conversion of rotational wind energy into divergent wind energy,which in turn converted kinetic energy back into available potential energy,thereby impeding the further development and maintenance of the southwest vortex.

Progress in ab initio in-medium similarity renormalization group and coupled-channel method with coupling to the continuum

Over the last decade,nuclear theory has made dramatic progress in few-body and ab initio many-body calculations.These great advances stem from chiral efective feld theory(xEFT),which provides an efcient expansion and consistent treatment of nuclear forces as inputs of modern many-body calculations,among which the in-medium similarity renormalization group(IMSRG)and its variants play a vital role.On the other hand,signifcant eforts have been made to provide a unifed description of the structure,decay,and reactions of the nuclei as open quantum systems.While a fully comprehensive and microscopic model has yet to be realized,substantial progress over recent decades has enhanced our understanding of open quantum systems around the dripline,which are often characterized by exotic structures and decay modes.To study these interesting phenomena,Gamow coupled-channel(GCC)method,in which the open quantum nature of few-body valence nucleons coupled to a deformed core,has been developed.This review focuses on the developments of the advanced IMSRG and GCC and their applications to nuclear structure and reactions.

SGG-DGCN:Wind Turbine Anomaly Identification by Using Deep Graph Convolutional Networks with Similarity Graph Generation Strategy

In order to minimize wind turbine failures,fault diagnosis of wind turbines is becoming increasinglyimportant,deep learning methods excel at multivariate monitoring and data modeling,but they are often limited toEuclidean space and struggle to capture the complex coupling between wind turbine sensors.To addressthis problem,we convert SCADA data into graph data,where sensors act as nodes and their topologicalconnections act as edges,to represent these complex relationships more efficiently.Specifically,a wind turbineanomaly identification method based on deep graph convolutional neural network using similarity graphgeneration strategy(SGG-DGCN)is proposed.Firstly,a plurality of similarity graphs containing similarityinformation between nodes are generated by different distance metrics.Then,the generated similarity graphs arefused using the proposed similarity graph generation strategy.Finally,the fused similarity graphs are fed into theDGCN model for anomaly identification.To verify the effectiveness of the proposed SGG-DGCN model,we conducted a large number of experiments.The experimental results show that the proposed SGG-DGCNmodel has the highest accuracy compared with other models.In addition,the results of ablation experimentalso demonstrate that the proposed SGG strategy can effectively improve the accuracy of WT anomalyidentification.

Transfer learning for well logging formation evaluation using similarity weights

Machine learning has been widely applied in well logging formation evaluation studies.However,several challenges negatively impacted the generalization capabilities of machine learning models in practical imple-mentations,such as the mismatch of data domain between training and testing datasets,imbalances among sample categories,and inadequate representation of data model.These issues have led to substantial insufficient identification for reservoir and significant deviations in subsequent evaluations.To improve the transferability of machine learning models within limited sample sets,this study proposes a weight transfer learning framework based on the similarity of the labels.The similarity weighting method includes both hard weights and soft weights.By evaluating the similarity between test and training sets of logging data,the similarity results are used to estimate the weights of training samples,thereby optimizing the model learning process.We develop a double experts’network and a bidirectional gated neural network based on hierarchical attention and multi-head attention(BiGRU-MHSA)for well logs reconstruction and lithofacies classification tasks.Oil field data results for the shale strata in the Gulong area of the Songliao Basin of China indicate that the double experts’network model performs well in curve reconstruction tasks.However,it may not be effective in lithofacies classification tasks,while BiGRU-MHSA performs well in that area.In the study of constructing large-scale well logging processing and formation interpretation models,it is maybe more beneficial by employing different expert models for combined evaluations.In addition,although the improvement is limited,hard or soft weighting methods is better than unweighted(i.e.,average-weighted)in significantly different adjacent wells.The code and data are open and available for subsequent studies on other lithofacies layers.

基于双图神经网络的会话推荐算法

针对现有会话推荐算法缺乏对属性信息利用的问题,提出一种基于双图神经网络的会话推荐算法(SR-DGNN)。分别构建会话图和全局相似图学习项目的时序特征和内容特征表示,设计相似度图卷积网络(S-GCN)对全局相似图进行建模。设计基于注意力机制的融合策略对项目的特征表示进行聚合,获取会话的全局表示。综合考虑用户的长期和短期兴趣,预测用户偏好。在KKBOX和MIND两个数据集上进行了大量实验,实验结果表明,所提模型优于现有基准模型。

经济与情感:后现代消费中乡村民宿空间符号建构的双重逻辑及机制

后现代消费中民宿作为乡村旅游重要的消费场所和空间,其符号消费现象客观存在,探讨其消费空间的符号生产与建构有助于乡村民宿产业的高质量发展。基于符号消费和空间生产理论,提出后现代消费中乡村民宿空间符号建构分析框架,并以成都明月村为案例地的分析发现:后现代消费中乡村民宿空间符号的生产建构是一个涉及多主体、多要素、多层次的符号化运作和互动展演过程;符号消费的经济逻辑和文化体验的情感逻辑是乡村民宿空间符号建构的双重逻辑,二者彼此权衡又互为补充,共同促进乡村民宿空间符号的可持续生产和建构;后现代消费中乡村民宿空间符号建构机制包括双重逻辑、符号建构过程、符号建构主体、符号建构路径等内容。

竞争对手技术相似性与技术能力的企业技术机会识别

[研究目的]在激烈的市场竞争中,企业如何实现高水平科技自立自强至关重要,在竞争对手视角下进行技术机会识别有助于企业实现创新突破,提升核心竞争力。[研究方法]构建技术相似性和技术能力二维矩阵选择竞争对手,在竞争对手视角下使用关联规则挖掘算法识别技术机会,最后利用对手关注度对技术机会进行评估,获取对手关注度较低的技术机会。[研究结果/结论]通过对比实验,证明在技术相似性与技术能力的基础上进行竞争对手选择能够提升识别机会的准确率。使用自然语言处理领域专利数据,以腾讯科技有限公司为例,识别出数据处理和计算模型、信息和通信技术应用、图像和视频处理与识别三个方向的技术机会,为企业的研发创新提供了参考依据。

基于锚点匹配和距离修正的轨迹相似性度量方法

轨迹相似性度量对群体移动模式分析与个性化位置服务推荐具有重要意义,现有方法未综合考虑轨迹点序列顺序与点对空间邻近性,导致对局部相似轨迹、逆序轨迹间的关系度量不准确。该文提出一种顾及轨迹全局空间分布和序列顺序的轨迹相似性度量方法,基于K近邻算法识别两条轨迹中空间相似度高的点对作为锚点,以划分区间约束其他点对匹配,并对受序列顺序约束无法匹配至空间邻近点的轨迹点进行距离修正,优化轨迹相似性计算。在深圳市515条人工标注轨迹数据上的验证结果表明,与改进的编辑距离、模糊最长公共子串和时空格网模型等8种方法相比,该方法在轨迹聚类任务中准确性提升2.8%~41.9%,并对轨迹长度、噪声和采样率变化具有较高的鲁棒性;此外,通过消融实验、特殊场景分析等证明了方法各步骤的有效性,并探讨了算法参数对精度的影响。研究结果可为轨迹聚类、轨迹检索等下游任务提供支撑。

基于相似度和密度的抗噪声船舶轨迹聚类方法

通过对船舶AIS数据聚类可以掌握船舶运动行为和特征规律,但在轨迹聚类中通过距离描述的相似性不能连续地表征轨迹之间的相似程度,且对轨迹中的噪声点敏感、无法区分轨迹方向。针对上述问题,本文提出一种基于相似度和密度的抗噪声轨迹聚类方法,构建航向约束分段路径距离并定义轨迹相似度函数;根据轨迹相似度分布特征和聚类评价指标,建立自适应确定最佳聚类参数流程。以长江口水域AIS数据为例,基于确定的最佳参数聚类出8个不同方向的轨迹簇,结果与实际船舶习惯航路相符。实验结果表明,所提出的方法能够快速确定最佳聚类参数并对不同运动方向的轨迹进行聚类,结果可用于特征轨迹提取和航路识别,为智能航海提供技术支撑。

长直坑道内爆炸冲击波相似规律研究

通过长直坑道内炸药爆炸后冲击波的超压峰值变化研究坑道内爆炸冲击波的相似规律。使用AUTODYN软件建立长直坑道仿真模型,采用映射方法将3.25 kg当量的球形TNT炸药在空气中的爆炸状态映射到长直坑道中,采用经典试验结果对模型进行验证。根据几何相似原理,通过改变坑道尺寸、坑道截面形状、炸点位置和炸药当量建立多组不同的模型,模拟计算得到坑道内爆炸冲击波的超压峰值,分析超压峰值的相似规律。结果表明,保持坑道截面积不变、改变截面形状及保持爆心距与炸药当量的比值不变、改变炸药当量,各模型计算得到的冲击波超压峰值具有相似规律。采用本文方法可对其他满足几何相似原理的坑道内爆炸冲击波参数进行预测,为地下空间设施的安全设计提供参考。

融合高阶组结构信息的节点分类算法

节点的局部邻域内通常存在具有特定局部连接模式且频繁出现的高阶组结构,这些组结构可以更准确地刻画节点拓扑特征,有助于理解网络的结构特征及节点间的交互模式。基于此,利用节点局部邻域内的高阶组结构特征计算节点间的结构相似性,并提出了一种融合高阶组结构信息的节点分类算法NHGS(Node Classification Algorithm Fusing High-order Group Structure Information)。该算法将k元组内形成的不同构的导出子图作为其初始组标签,利用Weisfeiler-Lehman(WL)算法迭代地聚合其邻域k元组的标签信息以更新k元组标签;节点在不同k元组标签中的出现次数构成了节点的特征向量,利用节点间特征向量的相似性表示节点间的结构相似性;结合节点的属性信息,并通过自编码器神经网络得到节点嵌入,进而对网络中的节点进行分类。NHGS将节点局部邻域内的k元节点组结构信息与节点的属性信息相结合,得到了包含高阶结构信息的节点表示。在真实属性网络上的实验表明,所提方法能有效计算出节点间的结构相似性,提升了节点分类任务的性能。