Complex Network Based Modeling and Analysis of Resource Nodes for MG

2014 ◽  
Vol 619 ◽  
pp. 332-336 ◽  
Author(s):  
Yong Yin ◽  
Chao Yong Zhang ◽  
De Jun Chen
Keyword(s):  
Complex Network ◽  
Network Model ◽  
Element Model ◽  
Optimal Composition ◽  
Manufacturing Grid ◽  
Modeling And Analysis ◽  
Static Parameter ◽  
Scale Free ◽  
Manufacturing Resource ◽  
Synchronization Performance

Manufacturing Grid (MG) is one of the most promising manufacturing modes in recent years, which has been proved to be a complex network characterized with scale-free. In this paper, the resource nodes of MG are treated as the nodes of a network and the linkage among each node is treat as the edges or arcs, based on which a three-element model of G = ( V, E, R) is proposed, and a scene of the optimal composition strategy among the 50 candidate nodes aiming at task A is modeled. Next the static parameter of the degree for a resource node and the synchronization performance of the complex network model for the resource nodes are studied. Results of the paper can promote the management of the manufacturing resource nodes and improve the efficiency of sharing MG resources, so as to facilitate the application and popularization of MG.

The Research of Complex Network on Archives Blog

2011 ◽  
Vol 181-182 ◽  
pp. 14-18
Author(s):  
Yi He
Keyword(s):  
Information Sharing ◽  
Complex Network ◽  
Network Model ◽  
Degree Distribution ◽  
Small World ◽  
Scale Free ◽  
Set Up

At the background of archives blog on Internet, this paper constructs a directed complex network model, and analyzes the network characters such as degree distribution. To verify its efficiency, we collect blogs’ information and set up a complex network..From the analysis result of the simulation and demonstration network, we know that they have the same characters, which show that, the virtual society network has small-world effect and scale-free character compared with real society network. The results indicate that the establishment of archives blog is favor to spread rapidly archives information, improve information sharing efficiency and promote the development of archives technology.

scholarly journals Modeling disease spreading on complex networks

2011 ◽  
Vol 8 (4) ◽  
pp. 1129-1141 ◽  
Author(s):  
Xiangjie Kong ◽  
Yu Qi ◽  
Xiumiao Song ◽  
Guojiang Shen
Keyword(s):  
Complex Network ◽  
Network Model ◽  
Virus Transmission ◽  
H1n1 Influenza ◽  
Contact Tracing ◽  
Contact Network ◽  
Cumulative Number ◽  
Scale Free ◽  
Disease Spreading ◽  
Peak Value

Based on complex network approach, a contact network model with scale-free property is built. By analyzing the fact data of H1N1 influenza provided by Beijing Health Bureau, contact tracing mechanism is used to research H1N1 virus transmission dynamics with this model. Furthermore, the contact tracing coefficient and random checking coefficient are studied to analyze their impact on the peak value of new infections and cumulative number of infections. The simulation result fits well with the statistical data. It shows that the model built in this paper is valid and complex network model to simulate the epidemics of H1N1 influenza is feasible.

scholarly journals Double Push Strategy of Knowledge for Product Design Based on Complex Network Theory

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Xue-rui Li ◽  
Sui-huai Yu ◽  
Jian-jie Chu ◽  
Deng-kai Chen ◽  
Lin-jian Wu
Keyword(s):  
Product Design ◽  
Complex Network ◽  
Network Model ◽  
Network Theory ◽  
Auxiliary Function ◽  
Triangular Fuzzy Number ◽  
Knowledge Network ◽  
Design Knowledge ◽  
Complex Network Theory ◽  
Scale Free

Reasonable application of design knowledge can help improve the efficiency and quality of product design. Based on complex network theory, this study proposes a double push strategy of knowledge for product design. The proposal introduces the concept of attribute similarity and triangular fuzzy number and uses the theory and method of complex network to build the knowledge network model for product design that contains creative knowledge subnetwork and engineering knowledge subnetwork. This paper is to understand the structure and dynamics of the knowledge network model and to identify and predict knowledge nodes and knowledge groups strongly related to design intent in view of the scale-free network topology analysis theory. We develop a double push strategy of product design knowledge to implement the effective auxiliary function for product design process. Finally, a design case of antalgic pump is presented to demonstrate the practicability and validity of the strategy.

The Selection of Manufacturing Grid Resources Node Based on the Model

2014 ◽  
Vol 926-930 ◽  
pp. 842-845 ◽  
Author(s):  
Fan Hua Hu ◽  
Hao You
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Clustering Coefficient ◽  
Manufacturing Grid ◽  
Intelligent Algorithm ◽  
Node Selection ◽  
Complex Network Theory ◽  
Manufacturing Resource ◽  
Grid Resources ◽  
Selection Of

The complex network model of the manufacturing grid was built based on complex network theory. Based on the model, the degree and its distribution, the mode dole, the average path length and clustering coefficient were studied. Taking an actual manufacturing task as example, the manufacturing resource node selection was performed integrated with the classical intelligent algorithm and the node selection performance is promoted. The research results are help to enhance the global optimization selection ability on the manufacturing resource node.

Study on Community Structures in Manufacturing Grid and the Algorithm for Community Partition of its Resource Nodes

2014 ◽  
Vol 526 ◽  
pp. 222-229 ◽  
Author(s):  
Yong Yin ◽  
Yu Li ◽  
Chao Yong Zhang
Keyword(s):  
Community Structure ◽  
Complex Network ◽  
Resource Sharing ◽  
Collaborative Design ◽  
Manufacturing Grid ◽  
Network Community ◽  
Design And Manufacturing ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Set Up

The Manufacturing Grid supplies a public platform for global resource sharing, collaborative design and manufacturing; its resource nodes constitute a complex network. Community partition of the complex network composed of the manufacturing resource nodes may be of some benefit for the sharing of manufacturing resources efficiently. In this paper, the resource nodes in the Manufacturing Grid are treated as the nodes of the complex network and the node-to-node link as its edges or arcs. The features of the resource nodes are analyzed based on which a model of the complex network composed of resource nodes in the Manufacturing Grid is set up. The nature phenomenon of the community structure in the complex network of manufacturing resource nodes is described according to the division of the manufacturing task into subtasks. Referring to Newmans idea, a criterion to evaluate the partition of community structure is discussed. Then, an improved algorithm based on Newman's Fast Algorithm is put forward to partition the community. The algorithm fully considers the characteristics of the direction and weight in the complex network for manufacturing resource nodes. Examples show that the algorithm presented in the paper can partition the community with favorable results.

scholarly journals A Novel BA Complex Network Model on Color Template Matching

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Risheng Han ◽  
Shigen Shen ◽  
Guangxue Yue ◽  
Hui Ding
Keyword(s):  
Complex Network ◽  
Network Model ◽  
Template Matching ◽  
Preferential Attachment ◽  
Color Space ◽  
Scale Free Network ◽  
Color Distribution ◽  
Scale Free ◽  
Matching Process ◽  
Free Network

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template’s color distribution. And then the template’s BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching.

scholarly journals Ripple-Spreading Network Model Optimization by Genetic Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Xiao-Bing Hu ◽  
Ming Wang ◽  
Mark S. Leeson
Keyword(s):  
Genetic Algorithm ◽  
Complex Network ◽  
Network Model ◽  
Real World ◽  
Network Models ◽  
Small World ◽  
Network Systems ◽  
Scale Free ◽  
Apply Genetic ◽  
Network Topologies

Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM) is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs) of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA) to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

Deep learning and complex network theory based analysis on socialized manufacturing resources utilisations and an application case study

2021 ◽  
pp. 1063293X2110031
Author(s):  
Maolin Yang ◽  
Auwal H Abubakar ◽  
Pingyu Jiang
Keyword(s):  
Deep Learning ◽  
Complex Network ◽  
Network Models ◽  
Neural Network Models ◽  
Complex Network Theory ◽  
New Type ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Resource Characteristics

Social manufacturing is characterized by its capability of utilizing socialized manufacturing resources to achieve value adding. Recently, a new type of social manufacturing pattern emerges and shows potential for core factories to improve their limited manufacturing capabilities by utilizing the resources from outside socialized manufacturing resource communities. However, the core factories need to analyze the resource characteristics of the socialized resource communities before making operation plans, and this is challenging due to the unaffiliated and self-driven characteristics of the resource providers in socialized resource communities. In this paper, a deep learning and complex network based approach is established to address this challenge by using socialized designer community for demonstration. Firstly, convolutional neural network models are trained to identify the design resource characteristics of each socialized designer in designer community according to the interaction texts posted by the socialized designer on internet platforms. During the process, an iterative dataset labelling method is established to reduce the time cost for training set labelling. Secondly, complex networks are used to model the design resource characteristics of the community according to the resource characteristics of all the socialized designers in the community. Two real communities from RepRap 3D printer project are used as case study.

Evaluation of invulnerability of scale-free networks using total information of local sub-graph

2018 ◽  
Vol 29 (08) ◽  
pp. 1850075
Author(s):  
Tingyuan Nie ◽  
Xinling Guo ◽  
Mengda Lin ◽  
Kun Zhao
Keyword(s):  
Mutual Information ◽  
Complex Network ◽  
Fundamental Problem ◽  
The Self ◽  
Practical Significance ◽  
Scale Free ◽  
Total Information ◽  
Scale Free Networks ◽  
Influential Nodes ◽  
Definition Of

The quantification for the invulnerability of complex network is a fundamental problem in which identifying influential nodes is of theoretical and practical significance. In this paper, we propose a novel definition of centrality named total information (TC) which derives from a local sub-graph being constructed by a node and its neighbors. The centrality is then defined as the sum of the self-information of the node and the mutual information of its neighbor nodes. We use the proposed centrality to identify the importance of nodes through the evaluation of the invulnerability of scale-free networks. It shows both the efficiency and the effectiveness of the proposed centrality are improved, compared with traditional centralities.

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