Advanced Materials Research Vols. 1049-1050

Abstract: In this paper, A mathematical model of two species with stage structure and distributed delays is investigated, the necessary and sufficient of the stable equilibrium point are studied. Further, by analyze the associated characteristic equation, it is founded that Hopf bifurcation occurs when τ crosses some critical value. The direction of Hopf bifurcation as well as stability of periodic solution are studied. Using the normal form theory and center manifold method.

Abstract: Lead, Mercury and Cadmium etc as the main evaluation index of heavy metal pollution established relational data model. The rough set theory is introduced, use the existing algorithm (Combinatorial Completer) to fill the missing value. After data preprocessing, use the DBMAS algorithm proposed in the paper to calculate the important degree of heavy metal pollution factors, in order to provides a more objective evaluation index weight for evaluation of heavy metal pollution.

Abstract: An algorithm of step adaptive normalization BSS(SAN-BSS) is proposed to solve the problem that the traditional switching BSS algorithms are sensitive to the types and the number of the source signals. The proposed algorithm improves the original ones’ stability by making use of the normalization mechanism to modify the cost functions, and realizes the adaptive updating of the step size by combining the signals’ separation process with the summation of the edge negentropy. The simulation results show that when the number of the source signals improves or the types of the signals change, the proposed algorithm can keep good separation effect. Compared with the original ones, the separation accuracy of our proposed algorithm improved 98%, and the number of iterations reduced nearly 60%, which improved the stability and the separation speed of the algorithm greatly.

Abstract: From numerous approaches studying the prediction of stock price, this paper proposed a new approach which was the combination of RBF neural network and Markov chain to forecast the stock closing price of the Shanghai composite index. Markov chain was aimed at making the error between the actual price and predicted price obtained by RBF neural network correct. Besides, for higher prediction accuracy, genetic algorithm was used to optimize the state division of Markov chain. The experimental result confirmed its effectiveness and superiority in comparison with the other two methods in some time interval.

Abstract: 3D model segmentation is a new research focus in the field of computer graphics. The segmentation algorithm of this paper is consistent segmentation which is about a group of 3D model with shape similarity. A volume-based shape-function called the shape diameter function (SDF) is used to on behalf of the characteristics of the model. Gaussian mixture model (GMM) is fitting k Gaussians to the SDF values, and EM algorithm is used to segment 3D models consistently. The experimental results show that this algorithm can effectively segment the 3D models consistently.

Abstract: In the era of big data, due to the rapid expansion of the data, the existing incremental text clustering algorithm has the drawback that the efficiency of algorithm will sharp decline with the time and data volume increasing. Because of poor timeliness and robustness, the algorithms are hard to be applied in practice. In this paper, we propose a distributed model framework of Single-Pass algorithm based on MapReduce, the experiments result of increment text cluster is accuracy, the algorithm effectively improve the computing efficiency of the algorithm and real-time of result. Algorithm has a great prospect under the background of big data.

Abstract: In reality, there are varieties of practical problems which are all optimizing many objectives at the same time. Meanwhile, these problems are usually highly complex, which are called multi-objective optimization problem. Multi-Objective Evolutionary Algorithms, shorted as MOEAs, is very suitable for solving this kind of problem. Chaos is defined as a random phenomenon with a sensitive dependence on initial conditions, which is produced by deterministic system. It covers almost each branch of both natural science and social science. The main work of this paper is to analyze and make conclusion about the dynamic chaotic mutation and MOEAs. Based on it, this paper proves the convergence of dynamic chaos multi-objective optimization, and proposes MOEAs based on dynamic chaotic mutation.

Abstract: We investigate two multi-frequency delta-kicked models for the quantum ratchet effect, in which a flashing multi-frequency potential periodically acts on a particle. Ratchet currents emerge when quantum resonances are excited. Currents in multi-frequency models may be stronger than those in the previous two-frequency model. Our work expands upon the quantum delta-kicked model and may contribute to experimental investigation of the quantum transport of cold atoms.

Abstract: We herein propose an efficient algorithm (called IWOSA herein after) hybridizing invasive weed optimization (IWO for short) with the simulated annealing (SA) algorithm. The IWO is a new algorithm proposed to solve actual practical problems, which imitates the invasive behavior of weeds in nature. In the further research IWO algorithm did not show its efficiency in high-dimensional problems, and lacked directivity in the process of IWOSA iterations. To deal with this problem, we employed IWO to provide diversity to explore solution and Metropolis criterion of SA to provide more precise guidance, and tried to improve accuracy and convergence speed by these steps. To test the proposed algorithm, we compared IWOSA with original IWO through high-dimensional optimization benchmark functions. The computational results showed the efficiency of our algorithm.

Abstract: Each object has its own specific properties, objects can be uniquely identified by its properties. "Properties" are properties of all the main features of the concept only, property values ​​are often given a certain amount of semantics, in the calculation of similarity among the different attributes if only to consider the type of calculation is obviously not complete [1]. For example: blue and blue, the similarity calculation in the property type, we can not determine its degree of similarity, but it is the same type of semantic expression under the different languages. Another example: domperidone and domperidone, which is the same type of drugs. Therefore, we attribute value in the calculation of the time, but also taking into account the semantic similarity.