An improved K-means algorithm application in evaluating interactive mechanism of airline industry ecosystem stability

Abstract

With the explosive growth of the mass data, the traditional architecture of the information system has been difficult to deal with enterprise needs. Data mining has become an important means of business innovation; it changed the development direction of cloud computing and also lead software-as-a-service (SaaS) becomes the main indicator of the era of cloud 2.0. This paper proposed an improved K-means algorithm, and uses it to evaluate interactive mechanism of airline industry ecosystem stability. Aiming at the clustering instability problem of traditional K-means algorithm in the process of random selection, this paper proposes a stochastic selection method for clustering centers initialization, the efficiency of the algorithm also has been greatly improved. By using data mining method, we make analysis of the ecological stability system of aviation industry; the result shows that technological innovation is the source of system stability, so it is the key link to the stability of the industrial ecosystem.