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(pP...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.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
Cultural landscape zoning research of traditional villages is the basic premise for carrying out overall protection and regional development.Through the clustering algorithm,cultural area zoning research of traditiona...Cultural landscape zoning research of traditional villages is the basic premise for carrying out overall protection and regional development.Through the clustering algorithm,cultural area zoning research of traditional villages can provide objective basis for its overall protection and development.Based on the field research,drawing on the theory of cultural landscape,southwest Hubei is taken as the research object,and the index system of cultural landscape type division of traditional villages is constructed from three levels of culture,geography and village carrier.Adopting the multi-attribute weighted k-modes clustering algorithm,92 traditional villages in southwest Hubei are divided into three major types,which are the western Tujia cultural characteristic area,the southern Tujia-Miao cultural penetration area,and the northern multi-ethnic cultural mixed area,and the characteristics of each area are summarized.The regional characteristics of traditional villages in southwest Hubei at the cultural landscape level are analysed from a macro point of view,which provides a reference for more objective cognition of the distribution law of traditional villages in southwest Hubei,and carrying out the contiguous protection of traditional villages.展开更多
Graphs have been widely used in fields ranging from chemical informatics to social network analysis.Graph-related problems become increasingly significant,with subgraph matching standing out as one of the most challen...Graphs have been widely used in fields ranging from chemical informatics to social network analysis.Graph-related problems become increasingly significant,with subgraph matching standing out as one of the most challenging tasks.The goal of subgraph matching is to find all subgraphs in the data graph that are isomorphic to the query graph.Traditional methods mostly rely on search strategies with high computational complexity and are hard to apply to large-scale real datasets.With the advent of graph neural networks(GNNs),researchers have turned to GNNs to address subgraph matching problems.However,the multi-attributed features on nodes and edges are overlooked during the learning of graphs,which causes inaccurate results in real-world scenarios.To tackle this problem,we propose a novel model called subgraph matching on multi-attributed graph network(SGMAN).SGMAN first utilizes improved line graphs to capture node and edge features.Then,SGMAN integrates GNN and contrastive learning(CL)to derive graph representation embeddings and calculate the matching matrix to represent the matching results.We conduct experiments on public datasets,and the results affirm the superior performance of our model.展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
In the past few decades,the navigation performance of ships and structures in ice-covered waters has not been fully studied,especially the influence of ice mechanical properties on icebreaking ability.Ice bending stre...In the past few decades,the navigation performance of ships and structures in ice-covered waters has not been fully studied,especially the influence of ice mechanical properties on icebreaking ability.Ice bending strength is a key ice parameter for predicting ship ice loads,and accurate ice bending strength is also the key to scaling model tests results to real ship.However,numerical simulation studies on model ice bending strength of ice tanks are often neglected.In this paper,an explicit finite element method model is used to simulate the ice cantilever beam test,and the failure load and bending strength of the ice are obtained.In this model,the Tsai-Wu failure criterion is used as the material constitutive model,and the required simulation parameters are obtained from the model ice test in ice tank.Parameter sensitivity analysis shows that the cantilever beam size of the model ice has a significant effect on the flexural strength.The results show that proper rounding at the root of the cantilever beam is beneficial to reduce stress concentration and obtain more accurate bending strength;the thickness,width and length of the cantilever beam should conform to a certain ratio,and consistent with the ITTC recommended reference.Therefore,the results of this study can promote model ice experiments and numerical studies and provide ice strength data support for ship design and polar ship maneuvering.展开更多
Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-sof...Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-softening (SS) rock masses. This study proposes a novel analytical model to determine the GRCs of SS rock masses, incorporating ground reinforcement and intermediate principal stress (IPS). The SS constitutive model captures the progressive post- peak failure, while the elastic-brittle model simulates reinforced rock masses. Nine combined states are innovatively investigated to analyze plastic zone development in natural and reinforced regions. Each region is analyzed separately, and coupled through boundary conditions at interface. Comparison with three types of existing models indicates that these models overestimate reinforcement effects. The deformation prediction errors of single geological material models may exceed 75%. Furthermore, neglecting softening and residual zones in natural regions could lead to errors over 50%. Considering the IPS can effectively utilize the rock strength to reduce tunnel deformation by at least 30%, thereby saving on reinforcement and support costs. The computational results show a satisfactory agreement with the monitoring data from a model test and two tunnel projects. The proposed model may offer valuable insights into the design and construction of reinforced tunnel engineering.展开更多
The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a mult...The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.展开更多
Hydraulic fracture(HF)formed in rock significantly helps with the development of geo-energy and georesources.The HF formation condition was challenging to understand,with obscure rock micro-cracking mechanisms being a...Hydraulic fracture(HF)formed in rock significantly helps with the development of geo-energy and georesources.The HF formation condition was challenging to understand,with obscure rock micro-cracking mechanisms being a key factor.The rock micro-cracking mechanism under gradient pore water pressure was analyzed on the scale of mineral particles and it was combined with macroscopic boundary conditions of rock hydraulic fracturing,obtaining the propagation criterion of HF in rock based on the rock micro-cracking mechanism which was verified by experiment.The results show that the disturbed skeleton stress induced by the disturbance of gradient pore water pressure in rock equals the pore water pressure difference.The overall range of the defined mechanical shape factor a/b is around 1,but greater than0.5.Under the combined influence of pore water pressure differences and macroscopic boundary stresses on the rock micro-cracking,micro-cracks form among rock mineral particles,micro-cracks connect to form micro-hydraulic fracture surfaces,and micro-hydraulic fracture surfaces open to form macrohydraulic fractures.HF begins to form at the micro-cracking initiation pressure(MCIP),which was tested by keeping the HF tip near the initiation point.The theoretical value of MCIP calculated by the proposed propagation criterion is close to MCIP tested.展开更多
In this paper,we study normal families of meromorphic functions.By using the idea in[16],we obtain some normality criteria for families of meromorphic functions concerning the wandering multiple functions,which extend...In this paper,we study normal families of meromorphic functions.By using the idea in[16],we obtain some normality criteria for families of meromorphic functions concerning the wandering multiple functions,which extend and improve the well-known Montel's criterion,Bloch-Valiron's theorem,and the related results due to Carathéodory,and Grahl-Nevo et al..展开更多
This study investigates the instability characteristics of dynamic disasters resulting from disruption caused by extracting resources underground. Utilizing the split Hopkinson pressure bar (SHPB) system, the dynamic ...This study investigates the instability characteristics of dynamic disasters resulting from disruption caused by extracting resources underground. Utilizing the split Hopkinson pressure bar (SHPB) system, the dynamic response mechanism of coal energy evolution is examined, and the energy instability criterion is established. The validity of the instability criterion is explored from the standpoint of damage progression. The results demonstrate that the energy conversion mechanism undergoes a fundamental alternation under impact disturbance. Moreover, the energy release rate as well as the energy dissipation rate undergo comparable changes across distinct levels of impact disturbance. The distinction between the energy release rate and the energy dissipation rate (DRD) increases as coal mass deformation grows. Prior to coal facing instability and failure, the DRD experienced an inflection point followed by a sharp decrease. In conjunction with the discussion on the damage evolution, the physical and mechanical significance of DRD remains clear, which can essentially describe the whole impact loading process. The phenomenon that the inflection point appears and DRD subsequently suddenly decreases can be employed as the energy criterion prior to the failure of instability. Furthermore, this paper provides significant reference for the prediction of dynamic instability of coal under dynamic disturbance.展开更多
This paper presents a new criterion for determining the unloading points quantitatively and consistently in a multi-stage triaxial test.The radial strain gradient(RSG)is first introduced as an arc tangent function of ...This paper presents a new criterion for determining the unloading points quantitatively and consistently in a multi-stage triaxial test.The radial strain gradient(RSG)is first introduced as an arc tangent function of the rate of change of radial strain to time.RSG is observed to correlate closely with the stress state of a compressed sample,and reaches a horizontal asymptote as approaching failure.For a given rock type,RSG value at peak stress is almost the same,irrespective of the porosity and permeability.These findings lead to the development of RSG criterion:Unloading points can be precisely determined at the time when RSG reaches a pre-determined value that is a little smaller than or equal to the RSG at peak stress.The RSG criterion is validated against other criteria and the single-stage triaxial test on various types of rocks.Failure envelopes from the RSG criterion match well with those from single-stage tests.A practical procedure is recommended to use the RSG criterion:an unconfined compression or single-stage test is first conducted to determine the RSG at peak stress for one sample,the unloading point is then selected to be a value close to the RSG at peak stress,and the multi-stage test is finally performed on another sample using the pre-selected RSG unloading criterion.Generally,the RSG criterion is applicable for any type of rocks,especially brittle rocks,where other criteria are not suitable.Further,it can be practically implemented on the most available rock mechanical testing instruments.展开更多
The automotive industry increasingly relies on numerical simulations to predict the geometry and forming processes of complex curved parts.Accurate yield stress functions that cover a wide range of stress states,such ...The automotive industry increasingly relies on numerical simulations to predict the geometry and forming processes of complex curved parts.Accurate yield stress functions that cover a wide range of stress states,such as uniaxial tension,equi-biaxial tension,near-plane strain tension,and simple shear,are essential for implementing virtual manufacturing technologies.In this work,a new additive-coupled analytical yield stress function,CPN2025,is proposed to accurately describe plastic anisotropy under various loading conditions.CPN2025 integrates the Poly4 anisotropic yield criterion with the Hosford isotropic yield criterion under a non-associated flow rule.A non-fixed-exponent calibration strategy is introduced,overcoming the limitations of existing yield criteria that typically offer curvature adjustment with only positive or negative correlations.CPN2025 is compared with other non-associated yield functions,including SY2009,CQN2017,and NAFR-Poly4,to evaluate its performance in predicting the plastic anisotropy of DP490,QP1180,AA5754-O,and AA6016-T4.Results show that,while meeting convexity requirements,the additive-coupled approach not only provides greater flexibility than the multiplicative-coupled but also simplifies the acquisition of partial derivative information.CPN2025 delivers the highest accuracy in characterizing anisotropic yield behavior,particularly for near-plane strain tension and simple shear loadings.Additionally,incorporating more uniaxial tensile yield stress-calibrated material parameters significantly improves the prediction capacity of in-plane anisotropic behavior.The use of anisotropic hardening concepts enhances the model's capability to capture the subsequent yield behavior across the entire plastic strain range.展开更多
Currently,the design of advanced compressor blades has reached the full ThreeDimensional(3D)modeling stage.When analyzing the reasons for the failure of popular corner stall prediction criteria for axial compressors t...Currently,the design of advanced compressor blades has reached the full ThreeDimensional(3D)modeling stage.When analyzing the reasons for the failure of popular corner stall prediction criteria for axial compressors to predict the corner flow state in modern compressor3D blades with end-bend and composite bend-sweep characteristics,it is believed that,in addition to the dihedral angle factor in the corner,the variation of the dihedral angle along the flow path is an important factor that has not been considered to date.In light of this,this study first uses the characteristic effects of the diffuser on the deceleration and pressure increase in airflow to design a series of physical models of varying dihedral angle diffusers that are equivalent to compressors.Based on these models,a quantization parameter is established to characterize the development speed of the intersection of boundary layers at the corner under varying dihedral angle and adverse pressure gradient conditions.After combining this with the effects of secondary flow,a Modified diffusion factor DJ(MDJ)is developed to describe the development of corner flow from the leading edge of the blade to its trailing edge under varying dihedral angle conditions.Finally,based on a compressor cascade database,an improved criterion for predicting corner stall in axial compressors using the MDJ diffusion factor is proposed.The validation results,based on extensive experimental data of compressor blades,reveal that this improved criterion can significantly enhance the accuracy of corner stall predictions in the 3D blades of modern compressors compared to currently used prediction criteria,by taking into account the effects of variations in the dihedral angle.展开更多
The generalized Zhang-Zhu(GZZ)strength criterion was proposed as an extension to the Hoek-Brown criterion and the Mogi criterion.The introduction to mean normal stress results in a non-smooth and non-convex yield surf...The generalized Zhang-Zhu(GZZ)strength criterion was proposed as an extension to the Hoek-Brown criterion and the Mogi criterion.The introduction to mean normal stress results in a non-smooth and non-convex yield surface,which presents a challenge for updating plastic stress.Current research primarily focuses on modified smooth GZZ criteria or approximate solutions,which inevitably lead to increased computational costs or inaccuracies.In this paper,an accurate stress updating algorithm is proposed based on the original GZZ criterion.The algorithm operates entirely in the principal stress space,where numerical singularities at the intersection of yield surfaces are avoided by defining four different types of stress updating.This approach simplifies the GZZ criterion compared to its formulation in general stress space.The return mapping is employed to compute the updated stress and consistent stiffness matrix,facilitating calculations using both finite element implicit and explicit algorithms.Finally,the accuracy of the proposed method is validated using rock true triaxial test data and semianalytical solutions for stresses and displacement around a circular opening under the GZZ criterion.展开更多
An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attr...An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. An eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. Two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an MADM problem. The simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. Finally, a numerical example is given to show the feasibility and effectiveness of the method. The result shows that it is easier than other methods of integrating subjective and objective information.展开更多
In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternati...In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.展开更多
[Objective]The aim was to establish a multi-attribute decision making method and introduce its application in rice breeding.[Method]Based on the defined closeness degree among attributes,the difference degrees among a...[Objective]The aim was to establish a multi-attribute decision making method and introduce its application in rice breeding.[Method]Based on the defined closeness degree among attributes,the difference degrees among attributes were discussed.Furthermore,the weights of attributes were determined based on the difference degrees among the attributes.[Result]A multi-attribute decision making method based on difference degrees among attributes was established,the feasibility of applying it in rice breeding was also analyzed.[Conclusion]This study enriched the methods to determine attribute weights in multi-attribute decision making and provided the necessary theoretical support for selecting rice varieties scientifically and rationally.展开更多
To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation...To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.展开更多
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘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.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
基金Philosophy and Social Sciences Research Project of Hubei Provincial Department of Education(22D057).
文摘Cultural landscape zoning research of traditional villages is the basic premise for carrying out overall protection and regional development.Through the clustering algorithm,cultural area zoning research of traditional villages can provide objective basis for its overall protection and development.Based on the field research,drawing on the theory of cultural landscape,southwest Hubei is taken as the research object,and the index system of cultural landscape type division of traditional villages is constructed from three levels of culture,geography and village carrier.Adopting the multi-attribute weighted k-modes clustering algorithm,92 traditional villages in southwest Hubei are divided into three major types,which are the western Tujia cultural characteristic area,the southern Tujia-Miao cultural penetration area,and the northern multi-ethnic cultural mixed area,and the characteristics of each area are summarized.The regional characteristics of traditional villages in southwest Hubei at the cultural landscape level are analysed from a macro point of view,which provides a reference for more objective cognition of the distribution law of traditional villages in southwest Hubei,and carrying out the contiguous protection of traditional villages.
文摘Graphs have been widely used in fields ranging from chemical informatics to social network analysis.Graph-related problems become increasingly significant,with subgraph matching standing out as one of the most challenging tasks.The goal of subgraph matching is to find all subgraphs in the data graph that are isomorphic to the query graph.Traditional methods mostly rely on search strategies with high computational complexity and are hard to apply to large-scale real datasets.With the advent of graph neural networks(GNNs),researchers have turned to GNNs to address subgraph matching problems.However,the multi-attributed features on nodes and edges are overlooked during the learning of graphs,which causes inaccurate results in real-world scenarios.To tackle this problem,we propose a novel model called subgraph matching on multi-attributed graph network(SGMAN).SGMAN first utilizes improved line graphs to capture node and edge features.Then,SGMAN integrates GNN and contrastive learning(CL)to derive graph representation embeddings and calculate the matching matrix to represent the matching results.We conduct experiments on public datasets,and the results affirm the superior performance of our model.
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
文摘In the past few decades,the navigation performance of ships and structures in ice-covered waters has not been fully studied,especially the influence of ice mechanical properties on icebreaking ability.Ice bending strength is a key ice parameter for predicting ship ice loads,and accurate ice bending strength is also the key to scaling model tests results to real ship.However,numerical simulation studies on model ice bending strength of ice tanks are often neglected.In this paper,an explicit finite element method model is used to simulate the ice cantilever beam test,and the failure load and bending strength of the ice are obtained.In this model,the Tsai-Wu failure criterion is used as the material constitutive model,and the required simulation parameters are obtained from the model ice test in ice tank.Parameter sensitivity analysis shows that the cantilever beam size of the model ice has a significant effect on the flexural strength.The results show that proper rounding at the root of the cantilever beam is beneficial to reduce stress concentration and obtain more accurate bending strength;the thickness,width and length of the cantilever beam should conform to a certain ratio,and consistent with the ITTC recommended reference.Therefore,the results of this study can promote model ice experiments and numerical studies and provide ice strength data support for ship design and polar ship maneuvering.
基金Projects(52208382, 52278387, 51738002) supported by the National Natural Science Foundation of ChinaProject(2022YJS072) supported by the Fundamental Research Funds for the Central Universities,China。
文摘Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-softening (SS) rock masses. This study proposes a novel analytical model to determine the GRCs of SS rock masses, incorporating ground reinforcement and intermediate principal stress (IPS). The SS constitutive model captures the progressive post- peak failure, while the elastic-brittle model simulates reinforced rock masses. Nine combined states are innovatively investigated to analyze plastic zone development in natural and reinforced regions. Each region is analyzed separately, and coupled through boundary conditions at interface. Comparison with three types of existing models indicates that these models overestimate reinforcement effects. The deformation prediction errors of single geological material models may exceed 75%. Furthermore, neglecting softening and residual zones in natural regions could lead to errors over 50%. Considering the IPS can effectively utilize the rock strength to reduce tunnel deformation by at least 30%, thereby saving on reinforcement and support costs. The computational results show a satisfactory agreement with the monitoring data from a model test and two tunnel projects. The proposed model may offer valuable insights into the design and construction of reinforced tunnel engineering.
文摘The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.
基金supported by the National Key Research and Development Program of China (No.2021YFC2902102)the National Natural Science Foundation of China (Nos.52374103 and 52274013)。
文摘Hydraulic fracture(HF)formed in rock significantly helps with the development of geo-energy and georesources.The HF formation condition was challenging to understand,with obscure rock micro-cracking mechanisms being a key factor.The rock micro-cracking mechanism under gradient pore water pressure was analyzed on the scale of mineral particles and it was combined with macroscopic boundary conditions of rock hydraulic fracturing,obtaining the propagation criterion of HF in rock based on the rock micro-cracking mechanism which was verified by experiment.The results show that the disturbed skeleton stress induced by the disturbance of gradient pore water pressure in rock equals the pore water pressure difference.The overall range of the defined mechanical shape factor a/b is around 1,but greater than0.5.Under the combined influence of pore water pressure differences and macroscopic boundary stresses on the rock micro-cracking,micro-cracks form among rock mineral particles,micro-cracks connect to form micro-hydraulic fracture surfaces,and micro-hydraulic fracture surfaces open to form macrohydraulic fractures.HF begins to form at the micro-cracking initiation pressure(MCIP),which was tested by keeping the HF tip near the initiation point.The theoretical value of MCIP calculated by the proposed propagation criterion is close to MCIP tested.
文摘In this paper,we study normal families of meromorphic functions.By using the idea in[16],we obtain some normality criteria for families of meromorphic functions concerning the wandering multiple functions,which extend and improve the well-known Montel's criterion,Bloch-Valiron's theorem,and the related results due to Carathéodory,and Grahl-Nevo et al..
基金Projects(51934007,12072363,52004268) supported by the National Natural Science Foundation of ChinaProject(22KJD440002) supported by the Natural Science Fund for Colleges and Universities in Jiangsu Province,China。
文摘This study investigates the instability characteristics of dynamic disasters resulting from disruption caused by extracting resources underground. Utilizing the split Hopkinson pressure bar (SHPB) system, the dynamic response mechanism of coal energy evolution is examined, and the energy instability criterion is established. The validity of the instability criterion is explored from the standpoint of damage progression. The results demonstrate that the energy conversion mechanism undergoes a fundamental alternation under impact disturbance. Moreover, the energy release rate as well as the energy dissipation rate undergo comparable changes across distinct levels of impact disturbance. The distinction between the energy release rate and the energy dissipation rate (DRD) increases as coal mass deformation grows. Prior to coal facing instability and failure, the DRD experienced an inflection point followed by a sharp decrease. In conjunction with the discussion on the damage evolution, the physical and mechanical significance of DRD remains clear, which can essentially describe the whole impact loading process. The phenomenon that the inflection point appears and DRD subsequently suddenly decreases can be employed as the energy criterion prior to the failure of instability. Furthermore, this paper provides significant reference for the prediction of dynamic instability of coal under dynamic disturbance.
文摘This paper presents a new criterion for determining the unloading points quantitatively and consistently in a multi-stage triaxial test.The radial strain gradient(RSG)is first introduced as an arc tangent function of the rate of change of radial strain to time.RSG is observed to correlate closely with the stress state of a compressed sample,and reaches a horizontal asymptote as approaching failure.For a given rock type,RSG value at peak stress is almost the same,irrespective of the porosity and permeability.These findings lead to the development of RSG criterion:Unloading points can be precisely determined at the time when RSG reaches a pre-determined value that is a little smaller than or equal to the RSG at peak stress.The RSG criterion is validated against other criteria and the single-stage triaxial test on various types of rocks.Failure envelopes from the RSG criterion match well with those from single-stage tests.A practical procedure is recommended to use the RSG criterion:an unconfined compression or single-stage test is first conducted to determine the RSG at peak stress for one sample,the unloading point is then selected to be a value close to the RSG at peak stress,and the multi-stage test is finally performed on another sample using the pre-selected RSG unloading criterion.Generally,the RSG criterion is applicable for any type of rocks,especially brittle rocks,where other criteria are not suitable.Further,it can be practically implemented on the most available rock mechanical testing instruments.
基金financial support from the National Natural Science Foundation of China(Grant Nos.52305396,52371116,and 52375310)support of the research fellowship from the Alexander von Humboldt Foundation.
文摘The automotive industry increasingly relies on numerical simulations to predict the geometry and forming processes of complex curved parts.Accurate yield stress functions that cover a wide range of stress states,such as uniaxial tension,equi-biaxial tension,near-plane strain tension,and simple shear,are essential for implementing virtual manufacturing technologies.In this work,a new additive-coupled analytical yield stress function,CPN2025,is proposed to accurately describe plastic anisotropy under various loading conditions.CPN2025 integrates the Poly4 anisotropic yield criterion with the Hosford isotropic yield criterion under a non-associated flow rule.A non-fixed-exponent calibration strategy is introduced,overcoming the limitations of existing yield criteria that typically offer curvature adjustment with only positive or negative correlations.CPN2025 is compared with other non-associated yield functions,including SY2009,CQN2017,and NAFR-Poly4,to evaluate its performance in predicting the plastic anisotropy of DP490,QP1180,AA5754-O,and AA6016-T4.Results show that,while meeting convexity requirements,the additive-coupled approach not only provides greater flexibility than the multiplicative-coupled but also simplifies the acquisition of partial derivative information.CPN2025 delivers the highest accuracy in characterizing anisotropic yield behavior,particularly for near-plane strain tension and simple shear loadings.Additionally,incorporating more uniaxial tensile yield stress-calibrated material parameters significantly improves the prediction capacity of in-plane anisotropic behavior.The use of anisotropic hardening concepts enhances the model's capability to capture the subsequent yield behavior across the entire plastic strain range.
基金co-supported by the National Natural Science Foundation of China(No.52406041)the China Postdoctoral Science Foundation(No.2025M774200)the National Science and Technology Major Project of China(No.2019-Ⅱ-0003-0023)。
文摘Currently,the design of advanced compressor blades has reached the full ThreeDimensional(3D)modeling stage.When analyzing the reasons for the failure of popular corner stall prediction criteria for axial compressors to predict the corner flow state in modern compressor3D blades with end-bend and composite bend-sweep characteristics,it is believed that,in addition to the dihedral angle factor in the corner,the variation of the dihedral angle along the flow path is an important factor that has not been considered to date.In light of this,this study first uses the characteristic effects of the diffuser on the deceleration and pressure increase in airflow to design a series of physical models of varying dihedral angle diffusers that are equivalent to compressors.Based on these models,a quantization parameter is established to characterize the development speed of the intersection of boundary layers at the corner under varying dihedral angle and adverse pressure gradient conditions.After combining this with the effects of secondary flow,a Modified diffusion factor DJ(MDJ)is developed to describe the development of corner flow from the leading edge of the blade to its trailing edge under varying dihedral angle conditions.Finally,based on a compressor cascade database,an improved criterion for predicting corner stall in axial compressors using the MDJ diffusion factor is proposed.The validation results,based on extensive experimental data of compressor blades,reveal that this improved criterion can significantly enhance the accuracy of corner stall predictions in the 3D blades of modern compressors compared to currently used prediction criteria,by taking into account the effects of variations in the dihedral angle.
基金the financial support provided by the National Key R&D Program of China(Grant No.2022YFB2302102)the National Natural Science Foundation of China(Grant Nos.42472340 and 42072308).
文摘The generalized Zhang-Zhu(GZZ)strength criterion was proposed as an extension to the Hoek-Brown criterion and the Mogi criterion.The introduction to mean normal stress results in a non-smooth and non-convex yield surface,which presents a challenge for updating plastic stress.Current research primarily focuses on modified smooth GZZ criteria or approximate solutions,which inevitably lead to increased computational costs or inaccuracies.In this paper,an accurate stress updating algorithm is proposed based on the original GZZ criterion.The algorithm operates entirely in the principal stress space,where numerical singularities at the intersection of yield surfaces are avoided by defining four different types of stress updating.This approach simplifies the GZZ criterion compared to its formulation in general stress space.The return mapping is employed to compute the updated stress and consistent stiffness matrix,facilitating calculations using both finite element implicit and explicit algorithms.Finally,the accuracy of the proposed method is validated using rock true triaxial test data and semianalytical solutions for stresses and displacement around a circular opening under the GZZ criterion.
文摘An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. An eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. Two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an MADM problem. The simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. Finally, a numerical example is given to show the feasibility and effectiveness of the method. The result shows that it is easier than other methods of integrating subjective and objective information.
文摘In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.
基金Supported by the Science Research and Development Project of Nanning City(201002030B)~~
文摘[Objective]The aim was to establish a multi-attribute decision making method and introduce its application in rice breeding.[Method]Based on the defined closeness degree among attributes,the difference degrees among attributes were discussed.Furthermore,the weights of attributes were determined based on the difference degrees among the attributes.[Result]A multi-attribute decision making method based on difference degrees among attributes was established,the feasibility of applying it in rice breeding was also analyzed.[Conclusion]This study enriched the methods to determine attribute weights in multi-attribute decision making and provided the necessary theoretical support for selecting rice varieties scientifically and rationally.
基金supported by the Research Innovation Project of Shanghai Education Committee (08YS19)the Excellent Young Teacher Project of Shanghai University
文摘To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.
