Edge-balanced index sets of [C10m×Pm10(m≡2,5(mod6)) ]nested network graph

Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (7): 28-34.

Previous Articles Next Articles

Edge-balanced index sets of [C10m×Pm10(m≡2,5(mod6)) ]nested network graph

LIU Jinmeng1, LIU Jinkui1, ZHENG Yuge2

1.Henan College of Industry and Information Technology, Jiaozuo, Henan 454003, China
2.School of Mathematics and Information Science, Henan Polytechnic University, Jiaozuo, Henan 454003, China

Online:2016-04-01 Published:2016-04-19

幂圈嵌套网络图[C10m×Pm10(m≡2,5(mod6))]的边-平衡指数集

刘金萌1，刘金魁1，郑玉歌2

1.河南工业和信息化职业学院，河南焦作 454003

2.河南理工大学数学与信息科学学院，河南焦作 454003

Abstract

Abstract: To cope with the edge-balanced index sets of network graph labeling, on the basis of smaller power-cycle nested network graph, the edge-balanced index sets of [C10m×Pm10] nested network graph are investigated. A new concept of single-point sector subgraph is proposed. It reduces the difficulty labeling because of the novel design of the basic graph, nested-cycle subgraph with gear and single-point sector subgraph. The results show that the edge-balance index sets of [C10m×][Pm10] network graph when m is divided by 6, the remainders are 2 and 5 , and showing the proofs of the computational formulas and the construction of the corresponding graphs.

null

Key words: edge-friendly labeling, edge-balanced index set, [C10m×Pm10(m≡2,5(mod6))], single-point sector subgraph

摘要： 基于网络图边-平衡指数集标号问题，在较小次幂圈嵌套网络图的基础上，研究无限路[C10m×Pm10]网络图的边-平衡指数集。提出了单点扇形子图的新概念，利用基础图、带齿套圈子图、单点扇形子图设计新思路，再次降低了构造标号图的复杂程度。确定了当[m]模6余2和余5时，无限路[C10m×Pm10]网络图边-平衡指数集，并完成全部公式证明和图形的构造。

关键词: 边-友好标号, 边-平衡指数集, [C10m×, Pm10(m&equiv, 2,5(mod6))], 单点扇形子图

LIU Jinmeng1, LIU Jinkui1, ZHENG Yuge2. Edge-balanced index sets of [C10m×Pm10(m≡2,5(mod6)) ]nested network graph[J]. Computer Engineering and Applications, 2016, 52(7): 28-34.

刘金萌1，刘金魁1，郑玉歌2. 幂圈嵌套网络图[C10m×Pm10(m≡2,5(mod6))]的边-平衡指数集[J]. 计算机工程与应用, 2016, 52(7): 28-34.

[1]	ZHANG Bo, XU Liming, HUANG Zhiwei, YAO Xiaopeng. Multi-objective GANs Pareto Optimality Algorithm Using Gradient Strategy [J]. Computer Engineering and Applications, 2021, 57(9): 89-95.
[2]	ZHANG Qishan, CHEN Lulu. Slope One Algorithm Based on Grey Correlational Analysis by Method of Degree of Balance and Approach [J]. Computer Engineering and Applications, 2021, 57(9): 96-102.
[3]	WANG Yonggui, LI Qianyu. Hybrid Collaborative Filtering Recommendation Algorithm Based on KNN-GBDT [J]. Computer Engineering and Applications, 2021, 57(9): 103-108.
[4]	SUN Zeyu, XU Chen, SU Yanchao, LI Chuanfeng, NIE Yalin. CCRP：Cross-Layer-Sensing Clustering Routing Protocol in Fog Computing [J]. Computer Engineering and Applications, 2021, 57(9): 109-117.
[5]	DENG Lifang, DANG Jianwu, WANG Yangping, WANG Song. Steganalysis of Spatial Image Based on Hybrid Kernel Feature Mapping [J]. Computer Engineering and Applications, 2021, 57(9): 118-125.
[6]	HUANG Yilei, XIA Zhijie, WANG Yiming. Research on False Information Dissemination Model of Strong-Ties Social Media [J]. Computer Engineering and Applications, 2021, 57(9): 126-133.
[7]	YANG Chunxia, LI Xinxu, WU Jiajun, LIU Tianyu. Hierarchical Network Sentiment Classification Based on Attention Interaction Mechanism [J]. Computer Engineering and Applications, 2021, 57(9): 134-139.
[8]	MOU Qingping, ZHANG Ying, ZHANG Dongbo, WANG Xinjie, YANG Zhiqiao. Research on Visual Tracking Algorithm and Application of Target Loss Discrimination Mechanism [J]. Computer Engineering and Applications, 2021, 57(9): 140-147.
[9]	BAO Zhiqiang, XING Yu, LYU Shaoqing, HUANG Qiongdan. Improved YOLO V2 6D Object Pose Estimation Algorithm [J]. Computer Engineering and Applications, 2021, 57(9): 148-153.
[10]	SANG Jianghui, JIANG Haiyan. Multi-label Transfer Learning Algorithm Based on Joint Distribution Alignment [J]. Computer Engineering and Applications, 2021, 57(9): 154-161.
[11]	WANG Lin, CHAI Jiangyun. Research on Deep Neural Network in Multi-scene Vehicle Attribute Recognition [J]. Computer Engineering and Applications, 2021, 57(9): 162-167.
[12]	HUANG Dongyi, YANG Bing, WU Zihao, KUANG Jiayi, YAN Zeming. Spatio-Temporal Fully Connected Convolutional Neural Networks for Citywide Cellular Prediction [J]. Computer Engineering and Applications, 2021, 57(9): 168-175.
[13]	ZHAO Zhiyan, YANG Hua, HU Zhiwei, YU Haiping. Identification Model of Pests on Yuluxiang Pear Leaves Based on TACNN [J]. Computer Engineering and Applications, 2021, 57(9): 176-181.
[14]	ZHOU Lungang, SUN Yifeng, WANG Kun, WU Jiang, HUANG Weigui, LI Binglong. End to End Object Recognition Algorithm for Multi-attributes of Multi-values [J]. Computer Engineering and Applications, 2021, 57(9): 182-190.
[15]	ZHU Jian, LIU Peiyu, CHEN Bingfeng, CAI Ruichu. Image De-raining via Similar Patch Matching and Minimum Value Filtering [J]. Computer Engineering and Applications, 2021, 57(9): 191-198.

Edge-balanced index sets of [C10m×Pm10(m≡2,5(mod6)) ]nested network graph

幂圈嵌套网络图[C10m×Pm10(m≡2,5(mod6))]的边-平衡指数集

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics