Applied Mechanics and Materials Vols. 602-605

Abstract: This paper introduces Runge-Kutta method into the game decision model of advertising differential equation, and establishes the two-order Runge-Kutta and the four-order Runge-Kutta differential equation models to study the impact of new fashion product on the sales and the impact of supply chain on the overall performance. In order to verify the validity and reliability of the model, this paper uses the MATLAB software to design the algorithm of advertising promotion differential equation model, and gets the accounting system of three types of advertising sales, and uses this system to statistics the sales. From the results we can see, the popular goods and seasonal goods have the largest effect on the new development fashion goods sales in three types of advertising, so it should increase the advertising delivery in popular goods and seasonal goods to ensure the sales of new fashionable goods.

Abstract: With the continuous expansion of internet shopping, e-commerce platform is also increasing, which also contains a large number of sports consumer e-commerce platform. This paper introduces the concept of RBV into the sports consumer e-commerce platform, and optimizes the design of the platform by using nonlinear fitting principle, finally obtains the basic structure of sports consumption e-commerce platform. In order to verify the validity and reliability of the platform, this paper uses Rebuild function of VC software to debug platform algorithm. Through calculation it is found that the nonlinear fitting algorithm designed in this paper is more stable than the general algorithm, and its stability is above 90%, which is accord with the design requirements. It provides a new computer method for the studying sports consumption.

Abstract: Compressed sensing is referred to as the CS technology; it can realize image compression and reconstruction process in low sample rate. It has great potential to reduce the sampling rate and improve the quality of image processing. In this paper, we introduce the structure prior model into the compressed sensing and image processing, and make the image reconstruction of high dimensional optimization process simplified into a series of low dimensional optimization process, which improves the processing speed and image quality. In order to verify the effectiveness and reliability of the proposed algorithm, this paper uses combined control form of C language and MATLAB software to design the programming of structure prior model, and use the Simulink environment to debug the program. Through the calculation we get the image block and the reconstruction result. It provides the technical reference for the research on image compressed sensing technology.

Abstract: Matlab tools are used to improve the programming in the process of calculation and analysis by adopting the continuous and discrete numerical methods developed in modern times with the variational principles and the subdivision interpolation as the basis, so as to implement the finite element analysis of the module, which is one of the most important method to solve the calculation and analysis in the calculation of complex engineering by finite element method. Firstly, according to the development of finite element method, and the characteristics of point process, we analyze the fundamental characteristics of the finite element method. On the basis of this, combined with the Matlab visual programming GUI component, we has designed the improved calculation and analysis programming of finite element method. In order to verify the rationality of the process, triangular unit division method is used to carry out the empirical analysis. And the results show that this method is effective, and has very strong practicability.

Abstract: Data mining is the frontier research topic in the field of information processing and database technology, is recognized as one of the most promising key technologies. Data mining is a collection of statistics, machine learning, database, pattern recognition, artificial intelligence and other disciplines, which is a new inter-discipline. Data mining put more emphasis on discovering implicit knowledge in huge amounts of data and the scalability of the algorithm, and is a technology very close to the actual use, with high technical content, bigger implementation difficulty.

Abstract: with the rapid development of mobile communication and Internet to the popularization of mobile terminal interaction, more and more people cannot do without real-time information, and with the growing popularity of mobile terminal and the performance and function of people constantly improve the requirements of mobile terminal is also more and more high. Instant communication is applied technology based on internet protocol, it enables users to use different devices to communicate, it is the basic function of text chat. Are not unified communication protocol is currently the major instant messaging software used. In recent years, the Android system because of its open source, easy development of widely used, it is mobile phone operating system platform based on open source Linux. XMPP is the instant communication protocol XML based on open source software, the content of XMPP is open and inherited XML characteristic.

Abstract: Noise multiple and user interference are the two important influencing factors that carrier synchronization technology in the wireless communication system faces. On the one hand, the phase locked loop and data aided carrier synchronization device is faced with poor estimation precision and slow convergence speed. On the other hand frequency offset and channel estimation problem need to be solved in multi-input multi-output (MIMO) communication system collaboration under the condition of dry low signal to noise ratio. So research of carrier synchronization algorithm of low complexity, high precision in view of the low SNR and multi-user communication system is becoming an important issue. 1. Carrier synchronization technology in wireless communication system of low signal-to-noise ratio and multiuser

Abstract: Due to the short investment time of the new equipment, the materiel consumption and maintenance data is not much. As a result, its demand prediction belongs to the prediction of small sample data. Since general demand prediction methods are difficult to predict the materiel demand of new equipment, an applicable and efficient prediction method should be explored to solve the problem. Therefore, combining grey prediction theory and least square support vector machine and operating accumulative generation on the original data sequence to extract its deep law characteristic, the new equipment materiel demand prediction model based on Grey Least Square Support Vector Machine (GLSSVM) was established, and the model's parameters was optimized by SIWPSO. Finally an example was set using Neural Network, traditional LSVSM and GLSSVM to predict the materiel demand of new equipment X to verify the accuracy and effectiveness of GLSSVM. The result shows that the prediction precision of GLSSVM is superior to the other two methods.

Abstract: It is instructed by Extension study’s theories and methods,and combining the knowledge of Artificial Intelligence ,taking adventage of the method of Date Mining ,in sesearching of the rule which settling contradictions in the process of decision making,accordingly,set up extension model,finally settle contradictions.

Abstract: In order to provide better service for the users, this paper put forwards a new algorithm for network selection. Firstly, the algorithm acquires weights’ vectors by analytic hierarchy process (AHP), G-1, entropy weighting method (EW) and variable coefficient (VC). Then combine the weights’ vector according to the similarity of different methods. Finally select the target network with the best performance. The simulation results show that the proposed algorithm can provide subscribers with better quality of service.