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Chen R.-F.,Hunan Urban Construction College
Journal of Computational and Theoretical Nanoscience | Year: 2016

In this paper, we investigate the multiple attribute decision making problems with triangular linguistic information. Motivated by the ideal of Bonferroni mean, we develop the aggregation techniques called the triangular linguistic Bonferroni mean (TLBM) operator for aggregating the triangular linguistic information. We study its properties and discuss its special cases. For the situations where the input arguments have different importance, we then define the triangular linguistic weighted Bonferroni mean (TLWBM) operator, based on which we develop the procedure for multiple attribute decision making under the triangular linguistic environments. Finally, a practical example for evaluating the engineer project risk is given to verify the developed approach and to demonstrate its practicality and effectiveness. © Copyright 2016 American Scientific Publishers All rights reserved.

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.

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.

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.

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.

Tang J.,Hunan Urban Construction College
Journal of Convergence Information Technology | Year: 2011

In this paper, two phase clustering algorithm is adopted to identify and track event. The first phase clustering is incremental clustering algorithm, and the new event will be identified. The second phase clustering is refined clustering algorithm, and the new event will be group and tracking. Experimental result shows that event identification and tracking using two phase clustering algorithm is effective.

Liu X.L.,Hunan Urban Construction College
Advanced Materials Research | Year: 2014

With the increasing development of society and the economy, the concept of green construction gradually attracts the much attention, and has been more widely used. In the green construction process, materials and energy-saving is a very important aspect. The rapid development in information technology today, information technology in all walks of life have been fully applied. The digital technology has provided us with the opportunity of a construction design in a virtual environment. This paper first describes the concept of green construction, and then expounds the specific of technology on utilization of green construction material-saving and material resources,through combining with specific examples, expounds the specific benefits of green construction. © (2014) Trans Tech Publications, Switzerland.

Wang K.,Hunan Urban Construction College
International Journal of Wireless and Mobile Computing | Year: 2016

In this paper, we propose a New Artificial Bee Colony (NABC) algorithm to enhance the search ability of onlooker bees. In NABC, the employed bees and onlooker bees utilise different search strategies to generate new candidate solutions. Moreover, NABC does not use the roulette selection, and a new method is designed to select good solutions for the onlooker bees. Experiments on some famous test functions show that the NABC algorithm outperforms some similar ABC and swarm intelligence algorithms. © Copyright 2016 Inderscience Enterprises Ltd.

Tang J.,Hunan Urban Construction College
Communications in Computer and Information Science | Year: 2011

We proposed an improved digital watermarking algorithm based on random sequence into reversible watermarking algorithm. Therefore, this method will use the robust watermarking algorithm of the well-known random sequence as embedding approach. Sobel edge detection algorithm is employed to extract the pixel value of edges from the watermarked image. And the final watermarked image is produced by replace the original image corresponding to the pixel value of the edges for the purpose of embedding watermark. Because the robust watermarking algorithm can tolerate the image which is destroyed to protect the copyright, there is no watermarking examination problem although this approach causes some loss of watermark information according to the experiment result. Moreover, it can not only examine whether the image has embedded watermarks, but also restore the original image. © 2011 Springer-Verlag Berlin Heidelberg.

Zhang Y.,Hunan Urban Construction College
Advanced Materials Research | Year: 2012

Genetic algorithm, particle swarm algorithm such as rise intelligence algorithm have unique advantages in multiple objective optimization areas, using the algorithm, based on architectural construction, materials, environment, climate, usage and features and other aspects of the overall optimization, can quickly and effectively realize the comprehensive effect of building energy efficiency optimization goal. This paper discusses the problem of multiple building energy efficiency, and for intelligent algorithm in building energy saving the optimization technology on the comprehensive introduction, finally how to particle swarm algorithm is applied to building energy efficiency optimization was attempted. © (2012) Trans Tech Publications, Switzerland.

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