Electric vehicles are widely embraced as a promising solution to reduce energy consumption and emission to achieve the Carbon Peak and Carbon Neutrality vision,especially in developing countries.Specifically,it’s vit...Electric vehicles are widely embraced as a promising solution to reduce energy consumption and emission to achieve the Carbon Peak and Carbon Neutrality vision,especially in developing countries.Specifically,it’s vital important to understand the ecological performance of electric vehicles and its association with driving behaviors under varying road and environmental conditions.However,current researches on ecological driving behavior mostly use structured data to reflect the characteristics of ecological driving behavior,and it is difficult to accurately reveal the recessive relationship between driving behavior and energy consumption.One promising and prevalent method for comprehensively and in-depth characterizing driving behaviors is“graph spectrums”,which allows for an effective and illustrative representation of complex driving behavior characteristics.This study presented an assessment method of ecological driving for electric vehicles based on the graph.Firstly,a multi-source refined data set was constructed through naturalistic driving experiments(NDE).Four typical traffic state(CCCF:congested close car-following;CSSF:constrained slow free-flow;CSCF:constrained slow carfollowing;UFFF:unconstrained fast free-flow)were classified through longitudinal acceleration data,and driving behavior graph was constructed to realize the visual representation of driving behavior.Then,the energy consumption graph was constructed using the energy loss of 100 km(EL)index.After the six drivers with the highest and lowest ecological assessment of driving behavior using the behavior graph and energy consumption graph,proposing the quantitative analysis of fifteen drivers'ecology driving behavior.The results show that:1)The graphical method can describe the individual features of a driver’s ecological driving behavior;2)Rapid acceleration of driving behavior leads to high energy consumption;3)In the comparison among the six ecodrivers and energy-intensive drivers,founding that the energy-intensive drivers accelerate and decelerate significantly more in CCCF traffic state;4)The driving behavior was more complex and unecological in CCCF traffic state;5)Fifteen drivers had lower ecological scores in start-up driving.This study proposes a method for visualizing ecology driving behavior that not only help understand the individual characteristics of ecological driving behaviors,but also offers substantial application value for the subsequent construction of Ecological driving behavior regulation models.展开更多
A subdivision vertex-edge corona G_1~S?(∪ G_3~E) is a graph that consists of S(G_1),|V(G_1)| copies of G_2 and |I(G_1)| copies of G_3 by joining the i-th vertex in V(G_1) to each vertex in the i-th copy of G_2 and i-...A subdivision vertex-edge corona G_1~S?(∪ G_3~E) is a graph that consists of S(G_1),|V(G_1)| copies of G_2 and |I(G_1)| copies of G_3 by joining the i-th vertex in V(G_1) to each vertex in the i-th copy of G_2 and i-th vertex of I(G_1) to each vertex in the i-th copy of G_3.In this paper, we determine the normalized Laplacian spectrum of G_1~S?(G_2~V∪ G_3~E) in terms of the corresponding normalized Laplacian spectra of three connected regular graphs G_1, G_2 and G_3. As applications, we construct some non-regular normalized Laplacian cospectral graphs. In addition, we also give the multiplicative degree-Kirchhoff index, the Kemeny's constant and the number of the spanning trees of G_1~S?(G_2~V∪ G_3~E) on three regular graphs.展开更多
The spectral theory of graph is an important branch of graph theory,and the main part of this theory is the connection between the spectral properties and the structural properties,characterization of the structural p...The spectral theory of graph is an important branch of graph theory,and the main part of this theory is the connection between the spectral properties and the structural properties,characterization of the structural properties of graphs.We discuss the problems about singularity,signature matrix and spectrum of mixed graphs.Without loss of generality,parallel edges and loops are permitted in mixed graphs.Let G1 and G2 be connected mixed graphs which are obtained from an underlying graph G.When G1 and G2 have the same singularity,the number of induced cycles in Gi(i=1,2)is l(l=1,l>1),the length of the smallest induced cycles is 1,2,at least 3.According to conclusions and mathematics induction,we find that the singularity of corresponding induced cycles in G1 and G2 are the same if and only if there exists a signature matrix D such that L(G2)=DTL(G1)D.D may be the product of some signature matrices.If L(G2)=D^TL(G1)D,G1 and G2 have the same spectrum.展开更多
Let D(G) =(d_(ij))_(n×n) denote the distance matrix of a connected graph G with order n, where d_(ij) is equal to the distance between vertices viand vjin G. A graph is called distance integral if all eigenvalues...Let D(G) =(d_(ij))_(n×n) denote the distance matrix of a connected graph G with order n, where d_(ij) is equal to the distance between vertices viand vjin G. A graph is called distance integral if all eigenvalues of its distance matrix are integers. In 2014, Yang and Wang gave a sufficient and necessary condition for complete r-partite graphs K_(p1,p2,···,pr)=K_(a1·p1,a2·p2,···,as···ps) to be distance integral and obtained such distance integral graphs with s = 1, 2, 3, 4. However distance integral complete multipartite graphs K_(a1·p1,a2·p2,···,as·ps) with s > 4 have not been found. In this paper, we find and construct some infinite classes of these distance integral graphs K_(a1·p1,a2·p2,···,as·ps) with s = 5, 6. The problem of the existence of such distance integral graphs K_(a1·p1,a2·p2,···,as·ps) with arbitrarily large number s remains open.展开更多
A graph G is called integral if all the eigenvalues of the adjacency matrix A（G） of G are integers. In this paper, the graphs G4（a, b） and Gs（a, b） with 2a ＋ 6b vertices are defined. We give their characteristi...A graph G is called integral if all the eigenvalues of the adjacency matrix A（G） of G are integers. In this paper, the graphs G4（a, b） and Gs（a, b） with 2a ＋ 6b vertices are defined. We give their characteristic polynomials from matrix theory and prove that the （n ＋ 2）-regular graphs G4（n, n＋ 2） and G5（n, n ＋ 2） are a pair of non-isomorphic connected cospectral integral regular graphs for any positive integer n.展开更多
Let G be a graph of order n and let λ1, λ2,...,λn be its eigenvalues. The Estrada index[2] of G is defined as EE = EE（G） =∑i=1^n e^λi.In this paper, new bounds for EE are established, as well as some relations ...Let G be a graph of order n and let λ1, λ2,...,λn be its eigenvalues. The Estrada index[2] of G is defined as EE = EE（G） =∑i=1^n e^λi.In this paper, new bounds for EE are established, as well as some relations between EE and graph energy E.展开更多
复杂电磁环境下卫星信号往往淹没在背景和噪声中,传统的信号检测算法在没有准确先验知识的情况下性能急剧降低,目前基于深度学习的信号检测算法往往需要依赖专家经验的数据后处理步骤,无法对信号进行端到端检测.针对上述缺陷,提出一种基...复杂电磁环境下卫星信号往往淹没在背景和噪声中,传统的信号检测算法在没有准确先验知识的情况下性能急剧降低,目前基于深度学习的信号检测算法往往需要依赖专家经验的数据后处理步骤,无法对信号进行端到端检测.针对上述缺陷,提出一种基于DETR_S(DEtection with TRansformer on Signal)的卫星信号智能检测方法.DETR_S以编码器-解码器架构为基础,利用Transformer网络全局建模能力捕获频谱信息,采用多头自注意力机制有效改善频谱信息长距离依赖的问题.基于匈牙利算法的预测框匹配模块摒弃了非极大值抑制的数据后处理步骤,将信号检测问题转变为集合预测问题,使模型并行输出检测结果.引入信号重构模块,将频谱重构损失函数加入损失函数中,辅助模型挖掘频谱深层表征,提升信号检测性能.实验结果表明,在仅使用信号频谱幅度信息条件下,DETR_S能够在信噪比等于0dB及以上对卫星信号进行精确检测(>95%),优于典型的目标检测方法.展开更多
基金supported by the National Key R&D Program of China(2023YFC3081700)the National Natural Science Foundation of China(52372341).
文摘Electric vehicles are widely embraced as a promising solution to reduce energy consumption and emission to achieve the Carbon Peak and Carbon Neutrality vision,especially in developing countries.Specifically,it’s vital important to understand the ecological performance of electric vehicles and its association with driving behaviors under varying road and environmental conditions.However,current researches on ecological driving behavior mostly use structured data to reflect the characteristics of ecological driving behavior,and it is difficult to accurately reveal the recessive relationship between driving behavior and energy consumption.One promising and prevalent method for comprehensively and in-depth characterizing driving behaviors is“graph spectrums”,which allows for an effective and illustrative representation of complex driving behavior characteristics.This study presented an assessment method of ecological driving for electric vehicles based on the graph.Firstly,a multi-source refined data set was constructed through naturalistic driving experiments(NDE).Four typical traffic state(CCCF:congested close car-following;CSSF:constrained slow free-flow;CSCF:constrained slow carfollowing;UFFF:unconstrained fast free-flow)were classified through longitudinal acceleration data,and driving behavior graph was constructed to realize the visual representation of driving behavior.Then,the energy consumption graph was constructed using the energy loss of 100 km(EL)index.After the six drivers with the highest and lowest ecological assessment of driving behavior using the behavior graph and energy consumption graph,proposing the quantitative analysis of fifteen drivers'ecology driving behavior.The results show that:1)The graphical method can describe the individual features of a driver’s ecological driving behavior;2)Rapid acceleration of driving behavior leads to high energy consumption;3)In the comparison among the six ecodrivers and energy-intensive drivers,founding that the energy-intensive drivers accelerate and decelerate significantly more in CCCF traffic state;4)The driving behavior was more complex and unecological in CCCF traffic state;5)Fifteen drivers had lower ecological scores in start-up driving.This study proposes a method for visualizing ecology driving behavior that not only help understand the individual characteristics of ecological driving behaviors,but also offers substantial application value for the subsequent construction of Ecological driving behavior regulation models.
基金Supported by the Young Scholars Science Foundation of Lanzhou Jiaotong University(Grant Nos.20160142017004+3 种基金 2017021)the Education Foundation of Gansu Province(Grant No.2017A-021)the National Natural Science Foundation of China(Grant Nos.11461038 61163010)
文摘A subdivision vertex-edge corona G_1~S?(∪ G_3~E) is a graph that consists of S(G_1),|V(G_1)| copies of G_2 and |I(G_1)| copies of G_3 by joining the i-th vertex in V(G_1) to each vertex in the i-th copy of G_2 and i-th vertex of I(G_1) to each vertex in the i-th copy of G_3.In this paper, we determine the normalized Laplacian spectrum of G_1~S?(G_2~V∪ G_3~E) in terms of the corresponding normalized Laplacian spectra of three connected regular graphs G_1, G_2 and G_3. As applications, we construct some non-regular normalized Laplacian cospectral graphs. In addition, we also give the multiplicative degree-Kirchhoff index, the Kemeny's constant and the number of the spanning trees of G_1~S?(G_2~V∪ G_3~E) on three regular graphs.
基金Quality Engineering Project of Anhui Province,China(No.2017zhkt036)
文摘The spectral theory of graph is an important branch of graph theory,and the main part of this theory is the connection between the spectral properties and the structural properties,characterization of the structural properties of graphs.We discuss the problems about singularity,signature matrix and spectrum of mixed graphs.Without loss of generality,parallel edges and loops are permitted in mixed graphs.Let G1 and G2 be connected mixed graphs which are obtained from an underlying graph G.When G1 and G2 have the same singularity,the number of induced cycles in Gi(i=1,2)is l(l=1,l>1),the length of the smallest induced cycles is 1,2,at least 3.According to conclusions and mathematics induction,we find that the singularity of corresponding induced cycles in G1 and G2 are the same if and only if there exists a signature matrix D such that L(G2)=DTL(G1)D.D may be the product of some signature matrices.If L(G2)=D^TL(G1)D,G1 and G2 have the same spectrum.
基金Supported by the National Natural Science Foundation of China（11171273） Supported by the Graduate Starting Seed Fund of Northwestern Polytechnical University（Z2014173）
文摘Let D(G) =(d_(ij))_(n×n) denote the distance matrix of a connected graph G with order n, where d_(ij) is equal to the distance between vertices viand vjin G. A graph is called distance integral if all eigenvalues of its distance matrix are integers. In 2014, Yang and Wang gave a sufficient and necessary condition for complete r-partite graphs K_(p1,p2,···,pr)=K_(a1·p1,a2·p2,···,as···ps) to be distance integral and obtained such distance integral graphs with s = 1, 2, 3, 4. However distance integral complete multipartite graphs K_(a1·p1,a2·p2,···,as·ps) with s > 4 have not been found. In this paper, we find and construct some infinite classes of these distance integral graphs K_(a1·p1,a2·p2,···,as·ps) with s = 5, 6. The problem of the existence of such distance integral graphs K_(a1·p1,a2·p2,···,as·ps) with arbitrarily large number s remains open.
基金Supported by the National Natural Science Foundation of China (10871158, 70871098)the Natural Science Basic Research Plan in Shaanxi Province of China (SJ08A01, 2007A09) and SRF for ROCS, SEM
文摘A graph G is called integral if all the eigenvalues of the adjacency matrix A（G） of G are integers. In this paper, the graphs G4（a, b） and Gs（a, b） with 2a ＋ 6b vertices are defined. We give their characteristic polynomials from matrix theory and prove that the （n ＋ 2）-regular graphs G4（n, n＋ 2） and G5（n, n ＋ 2） are a pair of non-isomorphic connected cospectral integral regular graphs for any positive integer n.
基金Supported by the National Natural Science Foundation of China(10771080)by the Fund of Fuzhou Uni-versity(XRC-0956)by the Natural Science Foundation of Fujian Province(2010J05005)
文摘Let G be a graph of order n and let λ1, λ2,...,λn be its eigenvalues. The Estrada index[2] of G is defined as EE = EE（G） =∑i=1^n e^λi.In this paper, new bounds for EE are established, as well as some relations between EE and graph energy E.
文摘复杂电磁环境下卫星信号往往淹没在背景和噪声中,传统的信号检测算法在没有准确先验知识的情况下性能急剧降低,目前基于深度学习的信号检测算法往往需要依赖专家经验的数据后处理步骤,无法对信号进行端到端检测.针对上述缺陷,提出一种基于DETR_S(DEtection with TRansformer on Signal)的卫星信号智能检测方法.DETR_S以编码器-解码器架构为基础,利用Transformer网络全局建模能力捕获频谱信息,采用多头自注意力机制有效改善频谱信息长距离依赖的问题.基于匈牙利算法的预测框匹配模块摒弃了非极大值抑制的数据后处理步骤,将信号检测问题转变为集合预测问题,使模型并行输出检测结果.引入信号重构模块,将频谱重构损失函数加入损失函数中,辅助模型挖掘频谱深层表征,提升信号检测性能.实验结果表明,在仅使用信号频谱幅度信息条件下,DETR_S能够在信噪比等于0dB及以上对卫星信号进行精确检测(>95%),优于典型的目标检测方法.
