, database and ETL operation, which can calculate a set of complete recommendation system from user operation end to server and data calculation. In order to improve the accuracy of the recommendation algorithm, this paper introduces k-means clustering algorithm to improve the recommendation algorithm based on user-based collaborative filtering.The experimental results show that the accuracy of the proposed algorithm has been significantly improved after the introduction of k-means.
International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 126–132
field includes the number of all victims and terrorists who directly caused death from terrorist incidents. We use only requires the number of victims and does not require the death toll of terrorists. Therefore, the number of victims is obtained by subtracting the number of terrorist deaths (nkiller) from the total number of deaths.
TERRORIST ATTACK HAZARD CLASSIFICATION MODEL
In this paper, the PCA algorithm, K-means clustering algorithm and entropy method are used to classify the
International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 81–85
detection accuracy of the above method is not high. In this paper, the Faster R-CNN[11-13] object detection algorithm is improved. The K-Means clustering algorithm is introduced to perform cluster analysis on the size of the object in the image, and the clustering results are directly input into the area recommendation network to achieve the improvement of the area recommendation network. Using Soft -The NMS algorithm replaces the NMS algorithm to reduce the miss detection probability of small
International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 76–82