The dynamic behaviors of a large-scale ring neural network with a triangular coupling structure are investigated.The characteristic equation of the high-dimensional system using Coate’s flow graph method is calculate...The dynamic behaviors of a large-scale ring neural network with a triangular coupling structure are investigated.The characteristic equation of the high-dimensional system using Coate’s flow graph method is calculated.Time delay is selected as the bifurcation parameter,and sufficient conditions for stability and Hopf bifurcation are derived.It is found that the connection coefficient and time delay play a crucial role in the dynamic behaviors of the model.Furthermore,a phase diagram of multiple equilibrium points with one saddle point and two stable nodes is presented.Finally,the effectiveness of the theory is verified through simulation results.展开更多
By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway a...By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway and its impact on the environment, which is adapted for the comprehensive assessment of railway environmental impact and the optimization of railway alignments. The assessment process of the GIS based map overlay method was presented, which includes deciding the system structure and weights of assessment factors, making environmental vulnerability grade maps, and evaluating the alternative alignments comprehensively to obtain the best one. With the GIS functions of spatial analysis, such as overlay analysis and buffer analysis, and functions of handling attribute data, the GIS based map overlay method overcomes the shortcomings of the existing map overlay method and the conclusion is more reasonable. In the end, a detailed case study was illustrated to verify the efficiency of the method.展开更多
Transmission line(TL)Parameter Identification(PI)method plays an essential role in the transmission system.The existing PI methods usually have two limitations:(1)These methods only model for single TL,and can not con...Transmission line(TL)Parameter Identification(PI)method plays an essential role in the transmission system.The existing PI methods usually have two limitations:(1)These methods only model for single TL,and can not consider the topology connection of multiple branches for simultaneous identification.(2)Transient bad data is ignored by methods,and the random selection of terminal section data may cause the distortion of PI and have serious consequences.Therefore,a multi-task PI model considering multiple TLs’spatial constraints and massive electrical section data is proposed in this paper.The Graph Attention Network module is used to draw a single TL into a node and calculate its influence coefficient in the transmission network.Multi-Task strategy of Hard Parameter Sharing is used to identify the conductance ofmultiple branches simultaneously.Experiments show that themethod has good accuracy and robustness.Due to the consideration of spatial constraints,the method can also obtain more accurate conductance values under different training and testing conditions.展开更多
The graph overlay method is used to evaluate the noise impact of route alignment and the results can serve as a reference for the route alignment optimal selection. The geographic information system(GIS), with its pow...The graph overlay method is used to evaluate the noise impact of route alignment and the results can serve as a reference for the route alignment optimal selection. The geographic information system(GIS), with its powerful function of handling attribute data and spatial analysis, is adopted to calculate the noise comprehensive impact area of each alignment. With the graph overlay method, the noise vulnerability and noise impact distribution are both taken into account in the noise impact assessment of route alignment. With GIS, the efficiency of work and the reliability of result are greatly improved. By a combination of them, the noise impact on environment is fully presented in a visual way and the assessment result has vital value in route alignment optimal selection. A detailed case study is illustrated and the efficiency of the method is verified.展开更多
Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been ...Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been employed to implement the RIS efficiently.However,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process.To address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)algorithm.The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning.By applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding values.This approach facilitates the learning of more hop layers within the GCN framework.The efficacy of the WF-GCN was demonstrated through its application to various datasets.In the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,respectively.Similarly,in the Last.FM dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,respectively.Furthermore,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.展开更多
Let G=(V,E)be a graph.For a vertex labeling f:V→Z2,it induces an edge labeling f+:E→Z2,where for each edge v1 v2∈E we have f+(v1 v2)=f(v1)+f(v2).For each i∈Z2,we use vf(i)(respectively,ef(i))to denote the number o...Let G=(V,E)be a graph.For a vertex labeling f:V→Z2,it induces an edge labeling f+:E→Z2,where for each edge v1 v2∈E we have f+(v1 v2)=f(v1)+f(v2).For each i∈Z2,we use vf(i)(respectively,ef(i))to denote the number of vertices(respectively,edges)with label i.A vertex labeling f of G is said to be friendly if vertices with different labels differ in size by at most one.The full friendly index set of a graph G,denoted by F F I(G),consists of all possible values of ef(1)-ef(0),where f ranges over all friendly labelings of G.In this paper,motivated by a problem raised by[6],we study the full friendly index sets of a family of cubic graphs.展开更多
In this paper, we study the inertial manifolds for a class of asymmetrically coupled generalized Higher-order Kirchhoff equations. Under appropriate assumptions, we firstly exist Hadamard’s graph transformation metho...In this paper, we study the inertial manifolds for a class of asymmetrically coupled generalized Higher-order Kirchhoff equations. Under appropriate assumptions, we firstly exist Hadamard’s graph transformation method to structure a graph norm of a Lipschitz continuous function, then we prove the existence of a family of inertial manifolds by showing that the spectral gap condition is true.展开更多
We consider the extraction of accurate silhouettes of foreground objects in combined color image and depth map data.This is of relevance for applications such as altering the contents of a scene,or changing the depths...We consider the extraction of accurate silhouettes of foreground objects in combined color image and depth map data.This is of relevance for applications such as altering the contents of a scene,or changing the depths of contents for display purposes in 3DTV,object detection,or scene understanding.To展开更多
In order to obtain a reduced methane combustion mechanism for predicting combustion field and pollutants accurately in CFD simulations with a lower computational cost,a reduced mechanism with 22 species and 65 steps o...In order to obtain a reduced methane combustion mechanism for predicting combustion field and pollutants accurately in CFD simulations with a lower computational cost,a reduced mechanism with 22 species and 65 steps of reactions from GRI-Mech 3.0 was obtained by direct relation graph method and sensitivity analysis.The ideal reactor calculation and VV&A(Verification,Validation,and Accreditation)in CFD were carried out using the proposed mechanism.The results showed that the proposed mechanism agrees well with the detailed mechanism in a wide range of operating conditions;the temperature field and species can be predicted accurately in CFD simulations(RANS and LES models),and the NO prediction error of an industrial gas turbine combustor outlet is less than 2×10-6.The proposed mechanism has high engineering values.展开更多
Catalan number is an important class of combinatorial numbers. The maximal outerplanar graphs are important in graph theory. In this paper some formulas to enumerate the numbers of maximal outerplanar graphs by means ...Catalan number is an important class of combinatorial numbers. The maximal outerplanar graphs are important in graph theory. In this paper some formulas to enumerate the numbers of maximal outerplanar graphs by means of the compressing graph and group theory method are given first. Then the relationships between Catalan numbers and the numbers of labeled and unlabeled maximal outerplanar graphs are presented. The computed results verified these formulas.展开更多
基金Supported by Natural Science Foundation of Shandong Province of China(Grant Nos.ZR2020MF080 and ZR2020MF065).
文摘The dynamic behaviors of a large-scale ring neural network with a triangular coupling structure are investigated.The characteristic equation of the high-dimensional system using Coate’s flow graph method is calculated.Time delay is selected as the bifurcation parameter,and sufficient conditions for stability and Hopf bifurcation are derived.It is found that the connection coefficient and time delay play a crucial role in the dynamic behaviors of the model.Furthermore,a phase diagram of multiple equilibrium points with one saddle point and two stable nodes is presented.Finally,the effectiveness of the theory is verified through simulation results.
文摘By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway and its impact on the environment, which is adapted for the comprehensive assessment of railway environmental impact and the optimization of railway alignments. The assessment process of the GIS based map overlay method was presented, which includes deciding the system structure and weights of assessment factors, making environmental vulnerability grade maps, and evaluating the alternative alignments comprehensively to obtain the best one. With the GIS functions of spatial analysis, such as overlay analysis and buffer analysis, and functions of handling attribute data, the GIS based map overlay method overcomes the shortcomings of the existing map overlay method and the conclusion is more reasonable. In the end, a detailed case study was illustrated to verify the efficiency of the method.
基金supported by the National Natural Science Foundation of PR China(42075130)the Postgraduate Research and Innovation Project of Jiangsu Province(1534052101133).
文摘Transmission line(TL)Parameter Identification(PI)method plays an essential role in the transmission system.The existing PI methods usually have two limitations:(1)These methods only model for single TL,and can not consider the topology connection of multiple branches for simultaneous identification.(2)Transient bad data is ignored by methods,and the random selection of terminal section data may cause the distortion of PI and have serious consequences.Therefore,a multi-task PI model considering multiple TLs’spatial constraints and massive electrical section data is proposed in this paper.The Graph Attention Network module is used to draw a single TL into a node and calculate its influence coefficient in the transmission network.Multi-Task strategy of Hard Parameter Sharing is used to identify the conductance ofmultiple branches simultaneously.Experiments show that themethod has good accuracy and robustness.Due to the consideration of spatial constraints,the method can also obtain more accurate conductance values under different training and testing conditions.
基金Project (2004036125) supported by Postdoctoral Science Foundation of China project(2002F008 2003F012) supportedby the Science and Technology Research and Development Planning Projects of the Ministry of Railway of China
文摘The graph overlay method is used to evaluate the noise impact of route alignment and the results can serve as a reference for the route alignment optimal selection. The geographic information system(GIS), with its powerful function of handling attribute data and spatial analysis, is adopted to calculate the noise comprehensive impact area of each alignment. With the graph overlay method, the noise vulnerability and noise impact distribution are both taken into account in the noise impact assessment of route alignment. With GIS, the efficiency of work and the reliability of result are greatly improved. By a combination of them, the noise impact on environment is fully presented in a visual way and the assessment result has vital value in route alignment optimal selection. A detailed case study is illustrated and the efficiency of the method is verified.
基金This work was supported by the Kyonggi University Research Grant 2022.
文摘Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been employed to implement the RIS efficiently.However,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process.To address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)algorithm.The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning.By applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding values.This approach facilitates the learning of more hop layers within the GCN framework.The efficacy of the WF-GCN was demonstrated through its application to various datasets.In the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,respectively.Similarly,in the Last.FM dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,respectively.Furthermore,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.
基金Supported by the National Natural Science Foundation of China(Grant No.11801149)Doctoral Fund of Henan Polytechnic University(Grant No.B2018-55)。
文摘Let G=(V,E)be a graph.For a vertex labeling f:V→Z2,it induces an edge labeling f+:E→Z2,where for each edge v1 v2∈E we have f+(v1 v2)=f(v1)+f(v2).For each i∈Z2,we use vf(i)(respectively,ef(i))to denote the number of vertices(respectively,edges)with label i.A vertex labeling f of G is said to be friendly if vertices with different labels differ in size by at most one.The full friendly index set of a graph G,denoted by F F I(G),consists of all possible values of ef(1)-ef(0),where f ranges over all friendly labelings of G.In this paper,motivated by a problem raised by[6],we study the full friendly index sets of a family of cubic graphs.
文摘In this paper, we study the inertial manifolds for a class of asymmetrically coupled generalized Higher-order Kirchhoff equations. Under appropriate assumptions, we firstly exist Hadamard’s graph transformation method to structure a graph norm of a Lipschitz continuous function, then we prove the existence of a family of inertial manifolds by showing that the spectral gap condition is true.
基金supported by Key Project No. 61332015 of the National Natural Science Foundation of ChinaProject Nos.ZR2013FM302 and ZR2017MF057 of the Natural Science Found of Shandong
文摘We consider the extraction of accurate silhouettes of foreground objects in combined color image and depth map data.This is of relevance for applications such as altering the contents of a scene,or changing the depths of contents for display purposes in 3DTV,object detection,or scene understanding.To
基金This work was supported by National Science and Technology Major Project(2017-Ⅲ-0006-0031)Fundamental Research Funds for the Central Universities(3072019CFJ0307)。
文摘In order to obtain a reduced methane combustion mechanism for predicting combustion field and pollutants accurately in CFD simulations with a lower computational cost,a reduced mechanism with 22 species and 65 steps of reactions from GRI-Mech 3.0 was obtained by direct relation graph method and sensitivity analysis.The ideal reactor calculation and VV&A(Verification,Validation,and Accreditation)in CFD were carried out using the proposed mechanism.The results showed that the proposed mechanism agrees well with the detailed mechanism in a wide range of operating conditions;the temperature field and species can be predicted accurately in CFD simulations(RANS and LES models),and the NO prediction error of an industrial gas turbine combustor outlet is less than 2×10-6.The proposed mechanism has high engineering values.
文摘Catalan number is an important class of combinatorial numbers. The maximal outerplanar graphs are important in graph theory. In this paper some formulas to enumerate the numbers of maximal outerplanar graphs by means of the compressing graph and group theory method are given first. Then the relationships between Catalan numbers and the numbers of labeled and unlabeled maximal outerplanar graphs are presented. The computed results verified these formulas.
