Applied Mechanics and Materials Vols. 513-517

Abstract: In this paper, we investigate the multi-attribute group decision making (MAGDM) problems in which all the information provided by the decision makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we utilize the induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision makers into a collective interval-valued intuitionistic fuzzy decision matrix. Based on the basic ideal of traditional VIKOR method, we establish an optimization model to determine the weights of attributes. Then, calculation steps based on the collective interval-valued intuitionistic fuzzy decision matrix and traditional VIKOR method for solving the MAGDM problems with interval-valued intuitionistic fuzzy assessments and partially known weight information are given. Finally, a numerical example is used to illustrate the applicability of the proposed approach.

Abstract: The prediction of the frequency non-selective WBAN fading channel behaviors is investigated. An novel WBAN prediction channel model is implemented based on Suzuki fading channel and Rice method and the parameters of the proposed model has been adjusted through MEA, MEDS, Jakes and Monte Carlo multipath simulation method. The performance evaluation for the adaptive WBAN channel model based on simulations is given. The validity of the proposed prediction model is confirmed by comparison of the first order statistics of the measured data.

Abstract: BP learning algorithm has advantage of simple structure, easy to implement and so on, it has gained wide application in the malfunction diagnosis and pattern recognition etc.. For BP algorithm is easy to fall into local minima shortcoming cites simulated annealing algorithm. Firstly, study the basic idea of BP learning algorithm and its simple mathematical representation; Then, research simulated annealing algorithm theory and annealing processes; Finally, the study makes BP algorithm combine with simulated annealing algorithm to form a hybrid optimization algorithm of simulated annealing algorithm based on genetic and improved BP algorithm, and gives specific calculation steps. The results show that the content of this study give full play to their respective advantages of two algorithms, make best use of the advantages and bypass the disadvantages, whether in academic or in the application it has a very important significance.

Abstract: BP neural network in character recognition, pattern classification, text and voice conversion, image compression, decision support and so on aspects has the widespread application, in view of the problems existing in the actual application, this paper researches learning algorithm and software implementation. Learning algorithm studies include three aspects, illustrates the basic thoughts of the BP algorithm, designed the three layers BP network structure, the mathematical model for the accurate description of algorithm. Software implementation studies include two aspects, the network model of all neurons become linked list structure and storage structure is designed, the design of the software process and will implement the process into four steps. BP algorithm of the software implementation is a basic work for the application of BP neural network, using the research results of this paper, the user can easily neural network design and simulation.

Abstract: Computer and information technology has evaded our every aspect of life. Information technology is seen in all aspect of the individual from banking and investing to shopping and communicating through the use of the internet services such as emails and chat rooms. Organizations and industries also utilize computer and information technology to collect information on individuals leading to the creation of warehouse of databases that enable them to achieve their objectives. In a distributed network environment today, information security is a very important issue in ensuring a safe computing environment.

Abstract: Manpower allocation determines the competence of the companies. Scientific manpower allocation calls for accurate evaluation on the abilities that the employees have for the posts. In this paper, we first present a general fuzzy clustering model for manpower evaluation for companies. To verify the approach, a new distance-based evaluation model is also presented. Simulation results demonstrated the accuracy of our research.

Abstract: On the basis of the image data characteristics, this study contrasted four kinds of data model. Then it analyzed the three kinds of implementation methods. It contrasts the management modes of the distributed image database finally.

Abstract: On the basis of the shortcoming of the existed algorithm, this paper probes into sliding windows pattern and introduces an efficient algorithm for data mining frequent pattern over sliding windows. A PSW-tree pattern is set in the algorithm to store frequent and critical pattern in data mining. On this basis, the paper presents a rapid mining algorithmPSW algorithm. In the experiment IBM data generator is used to produce generated data, which proves the validity and better space efficiency of the algorithm.

Abstract: Discrete element softwares that have been reported at home and abroad, normally calculate with fixed mechanical models. As the development of discrete element theory, users need more different mechanical models. Based on the three dimensional discrete element software developed by our team independently, mechanical model dynamic loading module has been added, which enables the software to meet the needs for different demands, and provides convenience for further development of wider range of applications.

Abstract: This paper describes the basic models of network security state evaluation system and concentrates on researching the situation assessment method with stochastic model. In the paper, which makes use of the Hidden Semi-Markov Model (HsMM), tries to simulate the operation of network system. The alert statistics, deriving from network defense system, is used as data sources to realize the evaluation of network security situation. HsMM modifies the HMM model concerning the hypothesis of some state-duration time in relation to exponential distribution, which coincides the description of the network systems operation in the real world. The experimental results imply that HsMM is an ideal security evaluation method.