Research On Node Centrality Recognition Based On Weighted TOPSIS

As a new and active research field,complex networks spread all over the lives of people,scientists have already introduced real-world networks into empirical research.At present,in the life science,computer science,management science,social science and many other fields,complex systems have been highly regarded by scientists.With the development of complex networks,People’s production and living standards have been greatly improved,but complex systems could have a negative impact on people’s lives at runtime.For example,the spread of diseases and rumors,large scale of power outages and paralysis of transportation networks.Therefore,we need to have a more in-depth understanding and analysis of complex networks to avoid or control the possible negative effects.Among the many research areas of complex networks the research of node centrality has become a very important and meaningful subject.There are already many methods of node centrality that have been proposed,however,some deficiencies are exist in these algorithms to some extent,so it is necessary for us to improve these algorithms to improve the effectiveness of evaluation.Based on the previous research,this paper proposes a new algorithm based on weighted TOPSIS model,the algorithm mainly solves the two problems as follows:firstly,TOPSIS centrality is a multi-index decision-making method,different algorithms of node centrality are taken into account,it can evaluate node centrality from multiple angles to overcome the one-sided problem exist in singularity index。Secondly,we use the method of entropy weight to assign weight to each centrality index,which overcomes the problem of equal weight distribution of TOPSIS centrality index in this paper.The SIR model is used to simulate the ability of node infection as quantitative index of node influence,we processed and analyzed the results with scatter plot and Kendall correlation coefficient,experiments show that the proposed method is superior to the three basic algorithms of Ks、CC and BC and the algorithm of TOPSIS centrality in community network.