Identifying node importance for networked systems in terms of the cascading model

The TOPSIS method identifies the spreading influences nodes by gathering different methods together with equal weights regardless the physics that different methods are effective for different scenarios. In this paper, by introducing the cascading model to measure the target node's influence, we present a weighted TOPSIS method by taking into 1% nodes cascading influence ability to calculate the weight. Experimental results for nine real-world networks show that, comparing with the traditional TOPSIS method, average speaking, accuracy of the WTOPSIS could be enhanced by 4.471%.