Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Policy Network Governance:Theory,Pattern,Strategy

Abstract: Policy network governance is a new school of governance research,which integrates the policy network theory and the governance theory.It differentiates with the bureaucracy and the market system and it has different theory and pattern,so it is a kind of public governance with new frame and new pattern,which manifests the deep variation in subjects,tools,structure,and mechanism of governance.But policy network also has the problem of governance failure,and the key of good governance is managing policy network efficiently and applying kinds of strategies to avoid the governance failure and to enhance the level of governance.

GPS Route Decisions Research Based on Network Theory

Abstract: Car GPS system is the most important function. Nowadays, the transport networks of a city become more and more complex, so that the traffic staggered become more complex. We proposed the approach on deciding the best path based on road conditions and user needs. It transforms the urban road traffic information in accordance with the objectives of the user-defined into equivalent road length indicators, and then take the road length indictors as the weight of grid edge. Then, a method of determining the best path was proposed, it accords road conditions and user needs to determine the minimum cost function, that is accord to user needs, using DIJKSTRA algorithm to get the best path for the GPS guide. In the last, we take 18 nodes transport network as an example, simulate the network use above algorithm. Simulation results demonstrate the effectiveness of the method.

A Novel Multi-Indicator Evaluation Algorithm for Identifying the Important Nodes in Complex Networks

Abstract: Identification of important nodes is an emerging hot topic in complex networks over the last few years. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness, closeness, etc. At present, most algorithms of important node evaluation are based on the single-indicator, which can’t reflect the whole condition of the complex network. Therefore, in this paper, after choosing multiple indicators from degree centrality, closeness centrality, eigenvector centrality, information centrality, density/clustering coefficient, mutual-information centrality, etc., and a new multi-indicator evaluation algorithm based on Locally Linear Embedding (LLE) for identifying important nodes in complex network is proposed. This proposed algorithm is compared with some single-indicator algorithms and other mainstream multi-indicator algorithms based on real-world networks. Through comprehensive analysis, the experimental results show that the proposed method ...

From Health Decisions to Performance: The Network Effect

Abstract: This study uses a simulation as a vehicle for social networks research application. Eighty five companies were created as part of a simulated healthcare industry. Our results suggest that companies positioning themselves at pivotal points within the network outperform companies that do not. The findings show the applicability of network theory and the use of simulations in applied research on healthcare decision-making.