Concerning the slow searching, poor practicability and being difficult to get a perfectly reasonable options of the methods for solving the problem of cloud services partner selection, a new partner selection method was proposed based on grey relational analysis and Particle Swarm Optimization (PSO) algorithm. Firstly, grey relational analysis method was used to select evaluation indexs of cloud providers, then the weight of each index value was calculated. Secondly, the mathematical model of services partner selection problems in cloud environment was built, then it was solved by using PSO algorithm to find the best partners. Performance test results of specific application examples show that the proposed method is feasible and rational, and can select the best partners.

In order to improve the detection accuracy of network intrusion, a network intrusion detection model named PSO-IG was proposed based on Particle Swarm Optimization (PSO) algorithm and Information Gain (IG). Firstly, PSO algorithm was used to eliminate redundant features of original network data, and then the weight values of selection features were obtained using IG, and Support Vector Machine (SVM) was used to establish intrusion detection model. Finally, the KDD CUP 99 dataset was used to test the performance of PSO-IG. The results show that the proposed model can eliminate redundant features and reduce the input dimension to improve the detection speed of network intrusion, and it can improve the network intrusion detection accuracy by reasonable selecting weight values.