Advanced Materials Research Vols. 1006-1007

Abstract: Antennas play an important role in RFID system. As one of the key technology of RFID, the antenna design decides the RFID system performance. This paper designed a ceramic Minkowski fractal antenna used in RFID system. It used Minkowski fractal structure as the radiation patch and the high performance ceramic material to reduce the antenna size, then improve it with rectangular joint structure in the antenna's ground plate. In this paper, the antenna performance are analyzed in the simulation, In this paper, the antenna performance are analyzed in the simulation, it discussed the thickness of the medium plate and the effect of dielectric constant on the performance of microstrip antenna, finally make antenna samples for testing. The simulation and test results show the antenna designed meet the requirement of RFID applications.

Abstract: A self-study harmony search (SSHS) algorithm for solving unconstrained optimization problems has presented in this paper . SSHS employs a novel self-study strategy to generate new solution vectors which can enhance accuracy and convergence rate of harmony search (HS) algorithm. SSHS algorithm as proposed, the harmony memory consideration rate (HMCR) is dynamically adapted to the changing of objective function value in the current harmony memory. a large number of experiments improved that SSHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its two improved algorithms (IHS and NGHS)

Abstract: By using tabu search algorithm which has strong local search ability as mutation operator of genetic algorithm, the tabu-genetic algorithm is designed for reactive power optimization in this paper, the strong global search ability of genetic algorithm and strong local search ability of tabu search algorithm is combined, the disadvantage of weak local search ability of genetic algorithm is conquered. Otherwise, the over limit of population is recorded and filtered, to ensure the final individual is under limit and effective. The tabu-genetic algorithm and simple genetic algorithm are used for simulation of IEEE 14-bus system 500 times, the results indicate that the performance of the tabu-genetic algorithm is much better than the simple genetic algorithm, its local search ability is improved obviously, and the active power loss is reduced more.

Abstract: A method by shifting chromaticity coordinates to immediately adjust the color temperature, hues and brightness of white-balance processed pictures in a digital camera was proposed. This method could be embedded into the firmware of an image processor to improve shortcomings of any white-balance algorithm. In addition, the picture took by a digital camera can be processed directly in the digital camera to obtain the desired color temperature, hues and brightness with no aids of image software.

Abstract: The stock market is a nonlinear dynamics system with enormous information, which is difficult to predict effectively by traditional methods. The model of stock price forecast based on BP Neutral-Network is put forward in this article. The paper try to find the way how to predictive the stock price. Exhaustive method is used for the hidden layer neurons and training method determination. Finally the experiment results show that the algorithm get better performance in stock price prediction.

Abstract: Recently, a new meta-heuristic optimization algorithm–harmony search (HS) was developed,which imitates the behaviors of music improvisation. Although several variants and an increasing number of applications have appeared, one of its main difficulties is how to enhance diversity and prevent it trapped into local optimal. This paper develops an opposition-based learning harmony search algorithm (OLHS) for solving unconstrained optimization problems. The proposed method uses the best harmony to play pitch adjustment, and bring the concept of opposition-base learning into improvisation, which enlarged the algorithm search space. Besides, we design a new parameter setting strategy to directly tune the parameters in the search process, and balance the process of exploitation and exploration. Numerical results demonstrate that the proposed algorithm performs much better than the existing HS variants in terms of the solution quality and the stability.

Abstract: In this paper, a new sufficient and necessary condition for judging block strictly-double diagonally dominant matrices is given firstly. By this theorem, some new practical criteria for nonsingular block H-matrices are obtained. In the end, the result effectiveness is illustrated by numerical examples.

Abstract: The concept of quasi-double diagonally dominant matrices is introduced, and it’s equivalent representation is given. As its application, one sufficient condition for nonsingular H-matrices is obtained. The effectiveness of the proposed criterion for nonsingular H-matrices is showed by numerical example.

Abstract: Compared with the intrusion detection based on pattern matching, the method which is based on model checking can detect the complex attacks. But all of the existing algorithms are used to detect some specific types of attacks. So, we firstly use the Interval Temporal Logic with Past Construct (ITLPC) formulae to set up formal sub-models respectively for the five kinds of attackers, the four kinds of attack processes and the eight kinds of attack effects. According to their universal relationship and the semantic relation of variety of ITLPC logic operators, we obtain the above sub-models together, thus, the universal models described by ITLPC formulae for universal attacks are formed. On this base, we implement an intrusion detection method based on ITLPC for detecting all types of attacks. Compared with the existing methods, the detecting ability of the new method is more comprehensive.

Abstract: We present a novel genetic-based algorithm for optimizing n-D simple-bounded continuous functions. In this paper, we propose a new mutation operator, called rotational mutation. The proposed approach starts from the vertices of the polytope created by the simple bounds, as the initial population. Similar to the conventional genetic algorithm, we calculate the optimum point of each population based on its cost value using the elitism mechanism. Then, we create the new generations based on the proposed rotational mutation and the conventional crossover operators. We have evaluated the algorithm on the two well-known test problems. Experimental results showed that the proposed approach outperforms the conventional genetic algorithm, in terms of the number of generations.