Entity

Time filter

Source Type


Tang J.,Hunan Urban Construction College
Applied Mechanics and Materials | Year: 2010

This paper presents an hybrid binary particle swarm optimization algorithm integration of genetic algorithms (HBPSO) to solve the RFID networks scheduling problems and get the optimal scheduling result in the problem. HBPSO is combined with advantages of binary PSO and GA. We use HBPSO to solve three problems of the RFID reader network and we attempt to minimize the total transaction time. By the results of the three problems, we can conclude that HBPSO is an effective algorithm which can find optimal solutions in the problem of the RFID reader network. © (2010) Trans Tech Publications, Switzerland. Source


Cheng N.,Hunan Urban Construction College
Journal of Convergence Information Technology | Year: 2012

Chaotic systems have many properties which can be connect with cryptography, such as pseudo-random, unpredictability of evolution of its orbits, properties of mixing and sensitivity to initial conditions and system parameters. Based on theoretical results on discrete chaos theory and cryptanalyses of several recently-proposed chaotic ciphers, we propose a discrete skew tent map to generate pseudo-random integer number sequences based on the key. According to the discrete sequences, gray value of image pixel is modified randomly, it is obvious that if attacker does not know the key, the encrypted image will be looked like white noise and cannot be rebuilt. In addition, we give statistical analysis, sequence random analysis, and sensitivity analysis to plaintext and key on the proposed scheme. The experimental results show the proposed cipher has higher security, faster encryption and lower computation expense as well as other good cryptographic properties. Source


Li H.,North China University of Technology | Jun T.,Hunan Urban Construction College
Journal of Convergence Information Technology | Year: 2012

One major problem in information retrieval is so many search results are similar or redundancy, this paper proposes enhanced search result using improved clustering algorithm for information retrieval. This method clusters the top 100 original search results, and then selects the search results from several clusters to present. Experimental result shows that the proposed algorithm is effective. It can avoid search results redundancy. Source


Li H.,North China University of Technology | Tang J.,Hunan Urban Construction College
Journal of Convergence Information Technology | Year: 2012

Differential evolution (DE) is a popular meta-heuristic optimizer which has shown good performance in solving many real-life and benchmark optimization problems. However, DE usually shows slow convergence rate at the last stage of the evolution. To enhance the performance of DE, this paper proposed an improved DE variant (OLSDE) which employs opposition-based concept and local search strategy. Experimental studies on several benchmark functions demonstrate that our approach outperforms standard DE and other two improved DE algorithms. Source


Tang J.,Hunan Urban Construction College
Journal of Convergence Information Technology | Year: 2010

This paper proposed improved K-means clustering algorithm based on user tag. It first used social annotation data to expand the vector space model of K-means. Then, it applied the links involved in social tagging network to enhance the clustering performance. Experimental result shows that the proposed improved K-means clustering algorithm based on user tag is effective. Source

Discover hidden collaborations