Applied Mechanics and Materials Vols. 644-650

Abstract: With the rapid development of communication industry in China from 2G to 4G networks, operators’ competition is intense in data flow business. Android mobile terminal is now widely used by people. Network traffic analysis is the premise to improve network speed and real needs of customers, excavate valuable information in vast amounts of data, and an important work for network providers analyzing flow rate and value. This paper mainly introduced the relevant contents of data mining, and data mining’s network traffic data analysis in Android mobile terminal.With the development of computer technology, network technology, and information technology, telecommunications enterprises accumulated a large amount of information resources and business data in the process of operation and management. How to find correlated, regular, and valuable information from these massive, disorderly, growing data is the problem facing enterprises, and data mining provides us with an effective solution.

Abstract: Network coding optimization method research based on genetic algorithm applies network coding technology in monophyletic multicast network. After reaching network multicast rate, find link coding scheme which makes the minimum of the total number of network coding. Moreover, it makes the analysis and improvement for general genetic algorithm’s defects in network coding link optimization such as rare individual successful decoded by randomly generated initial population strategies, reduced algorithm search ability, premature convergence of genetic algorithm and long algorithm running time.

Abstract: K - means algorithm is the classical algorithm to solve the problem of clustering in the area of data mining, when the sample data meets certain conditions, the results of clustering is better. But the algorithm is sensitive to the initial clustering center and clustering results will change as the differences of initial clustering center its number. Aimed at this shortage, this paper proposes a new algorithm based on prim algorithm to select the initial clustering center, details the basic idea of the algorithm and improves the specific methods and implementation steps, finally uses a test for the contrastive analysis. Results show that the improved K - means clustering algorithm needs not to specify the initial clustering center in advance, and it is not sensitive to abnormal value, and at the same time the use of greedy strategy makes the clustering effect more optimal than usual algorithms.

Abstract: To solve low precision of basic gravity aided matching algorithm caused by the influence of gravimetric map error, observed model linearization error, insufficiency observed quantity and so on, a novel algorithm of square root KF+CKF mixed filter algorithm based on Rao-Blackwellizationptive is proposed. The calculation accurary,speed, noise immunity, and application scope are improved by approximation local gravity field model using gauss spline interpolation,establishing nonliear mixed model viewing at gravity and position error, model decomposition using Rao-Blackwellization thoery,improving KF and CKF by changing error covariance matrix to square root model, adaptively adjusting filter renewal process.The result shows that it is less sensitive to INS initial error and nonlinearized degree of navigation system model with higher speed,better accurary and stronger robustness.

Abstract: Airborne dust aerosol plays an important role in the climate system, as it not only impacts global atmospheric climate directly or indirectly, but also influences human life and transportation. Satellites are increasingly used to obtain information on aerosol properties such as the aerosol optical depth. In this paper, dust AOD in Beijing is retrieved from the hyperspectral observed data of The Atmospheric Infra-Red Sounder (AIRS) by using singular value decomposition (SVD) decomposition method. As a result, the inversion by using SVD is good with ground-based observations of Aerosol Observation Network (AERONET) data, which shows that the algorithm is feasible, and can well distinguish from the influence of surface emissivity and gas absorption.

Abstract: Ant colony optimization algorithm (ACO) is a good method to solve complex multi-stage decision problems. But this algorithm is easy to fall into the local minimum points and has slowly convergence speed, According to the semantic relations, an improved ant colony algorithm has been proposed in this paper. In contrast with the tradition algorithm, the improved algorithm is added with a new operator to update crucial parameters. The new operator is to find out the potential semantic relations behind the history information based on ontology technology. Ant colony optimization can be applied to many engineering fields,taking the Traveling Salesman Problem (TSP) as example, Our experiments show accuracy of improved ant colony algorithm that is superior to that obtained by the other classical versions, and competitive or better than the results achieved by the compared algorithm, this improved algorithm also can improve the searching efficiency.

Abstract: Scheduling is generally believed to be a hard computational problem. People propose a lot of algorithms for solving this problem, most of which require exponential time. In this paper, we study a restricted form of scheduling problem, called the course scheduling problem. We show that this problem can be solved by reducing it to the network flow problem, which requires polynomial time to solve. Our proposed method is simple and efficient. It can scale up to real-world scheduling problems.

Abstract: In recent years, there has been a lot of interest on systems that process large amounts of data. The goal of data prediction is to take advantage of data history and predict new coming data. However, the result of data prediction may not be accurate enough due to uncontrollable factors. The goal of section data prediction is to use a section to predict new coming data so that the real value falls into the section with a good possibility. In this paper, we propose a method for section data prediction based on linear regression. Our experimental results show that this method can produce desirable results.

Abstract: This paper studies the accurate prediction problem of VRLA battery state of charge (SOC) and the remaining capability of the battery, after the comprehensive analysis of the various elements which affect the battery state of charge, we put forward a battery degradation test model based on GA - WNN, and carries on the verification test, in the meantime, we also make it contrast with other algorithms. The results of test show that the model of WNN Optimized by GA has shorter training time and high prediction accuracy, it can predict the battery remaining power more accurately.

Abstract: We make ​​a preliminary analysis of the process during pulsed laser damages CCD from the aspect of detector’s thermal effect by it.We build simulation model of CCD irradiated by laser.The simulation results show that silica damage energy density threshold range between 1-5.8 J/cm². This magnitude doesn’t appear to be much different from previous data. So it shows that simulation results are believable.