| Popis: |
In the space clustering algorithm, because of the choice of the value of k and the problem of the non-clear "elbow point" of the elbow method, this paper introduces logarithmic function and determines the initial clustering center on the basis of the properties of exponential function, weight adjustment, bigotry term and the basic idea of elbow method, and proposes an improved k-value selection algorithm. Combined with the fully adaptive spectral clustering algorithm, the global terrorist attack data are clustered. It effectively solves the problem that the selection of k value is not clear and the outlier can not be separated in the clustering process. The experimental results show that the clustering method proposed in this paper can not only determine the k value quickly and accurately, but also achieve better clustering effect. CesiumJS, WebVR and speech recognition technology are used to visually display and interact the results. |
