Advanced Materials Research Vols. 989-994

Abstract: Wireless sensor networks (WSN) have become a hot research topic in the field of computer science. Since WSNs are characterized by limited node energy, dynamic topological structure and data fusion, the design of WSN routing protocols is faced with new problems and challenges. In recent years, many new routing algorithms for wireless sensor networks have appeared, but they all have some shortcomings. This paper studies and analyzes these routing protocols, and in view of their shortcomings, proposes a WSN hierarchical routing protocol based on ant colony algorithm. And a simulation test is conducted on this improved routing protocol, and the simulation result proves that this algorithm basically achieves the design objectives of WSN routing algorithms.

Abstract: This paper proposes an analysis measure for Big Data by optimizing traditional data mining, base on Weka data analyzing platform ,K-means algorithm is employed through the interface programs in Weka system, so that optimized data mining techniques can be applied in cloud storage, cloud computing of Big Data by clustering analysis base on Big Data pre-processing and real-time monitoring of memory.

Abstract: In this paper, the author designed the model of instruction expert system based on improved genetic algorithm and described the realization of improving exercises in detail. In this system, the students can online learn through different modes and receive the guidance from the teacher, meanwhile the analysis to effect the parameter of intelligent tests generating will be produced. So the following exercises focus on the student’s weakness, this is useful to enhance the students’ the knowledge level and operation ability.

Abstract: In this paper, the problem of selecting investor is studied under dual uncertainty information, i.e. fuzzy information and grey information. Concretely, a new index system of evaluating the investors which includes sales capacity, management capacity, throughput, technology capacity, fund capacity, risk capacity and uniformity of enterprise strategy is designed, and then a model of dual uncertainty multi-attribute decision making is proposed. Moreover an optimization algorithm of fuzzy grey deviation degree is present to solve this model.

Abstract: In this paper ,we discuss multiobjective optimization problems solved by Memetic algorithms. We present A novel multiobjective memetic algorithm based on invasive weed optimization and differential evolution (IWO-DE) to solve this class of problems .We present the Nutrition Prescription Model for Meals.the IWO-DE is applied to solve the nutrition decision making problem to map the Pareto-optimum front. The results in the problem show its effectiveness.

Abstract: The genetic algorithm (GA) is a self-adapted probability search method used to solve optimization problems, which has been applied widely in science and engineering. In this paper, we propose an improved variable string length genetic algorithm (IVGA) for text clustering. Our algorithm has been exploited for automatically evolving the optimal number of clusters as well as providing proper data set clustering. The chromosome is encoded by special indices to indicate the location of each gene. More effective version of evolutional steps can automatically adjust the influence between the diversity of the population and selective pressure during generations. The superiority of the improved genetic algorithm over conventional variable string length genetic algorithm (VGA) is demonstrated by providing proper text clustering.

Abstract: With the rapid development and wide applications of information science and applied technology, nonlinear problems become an important direction of research in the field of numerical analysis. In this paper, we mainly study the iterative method for nonlinear equations. We propose and analyze a modified Newton-type method with order of convergence six for solving nonlinear equations. The method is free from second derivatives. The efficiency index of the presented method is 1.565, which is better than that of the classical Newton’s method 1.414. Some numerical experiments illustrate the efficiency and performance of the proposed method.

Abstract: AES (Advanced Encryption Standard) in May 26, 2002 became effective standard. AES algorithm research has become a hot topic at home and abroad, and the algorithm has been widely applied in the field of information security. Since the algorithm of AES key expansion part is open, so the key is between the wheel can be derived from each other, the AES algorithm designed for this security risk by generating pseudo-random number. Logistic mapping a certain length, after quantization is used as a key to improve the security of the AES algorithm.

Abstract: The CMA cost function is simplified to meet the second norm form, and a new CMA blind equalization based on quasi-newton algorithm is proposed. Since the CMA cost function does not meet the second norm form, it is difficult to use quasi-newton algorithm to update the blind equalizer directly based on the cost function of CMA. If the cost function is simplified to meet the second norm form, it can use quasi-newton algorithm to update the blind equalizer directly. Thus, the convergence rate and convergence precision of CMA blind equalization can be improved effectively. Simulation results under the acoustic channels show that CMA blind equalization with quasi-newton algorithm based on the simplified cost function has faster convergence rate and less steady state residual error, which has practical value in the blind equalization of fast time-varying underwater acoustic channels

Abstract: In this paper, an implementation of the complex-frequency-shifted perfectly matched layer (CPML) is developed for three-dimensional hybrid implicit-explicit (HIE) finite-difference time-domain (FDTD) method based on auxiliary differential equation (ADE). Because of the use of the ADE technique, this method becomes more straightforward and easier to implement. The formulations for the HIE-FDTD CPML are proposed. Numerical examples are given to verify the validity of the presented method. Results show that, both HIE-CPML and FDTD-CPML have almost the same reflection error, while their reflection error is about 30 dB, which is less than HIE Mur’s first-order results. The contour plots indicate that the maximum relative reflection as low as-72 dB is achieved by selecting and .