Advanced Materials Research Vols. 605-607

Abstract: Nonlinear system optimization is always an issue that needs to be considered in engineering practices and management. In order to obtain optimal solutions without analysis formulas to nonlinear systems, we first construct a radial-base-function (RBF) neural network using the newrb() function in MALTAB 7.0, then train the neural network according to input and output, and finally obtain the solution using a genetic algorithm. Simulated experimental results show that the proposed algorithm is able to achieve optimal solutions with a relatively fast speed of convergence.

Abstract: Based on Nagatani’s model, an extended car following model named flow and density difference lattice model (FDDLM) was proposed. Using the linear stability theory, the stability condition of the new model was obtained. The phase diagram presents that density difference effect is more efficiently than flow difference effect in improving the traffic flow stability and FDDLM could suppress traffic jam effectively. The numerical simulations are consonant with the analytical results and show that considering the flow and density difference leads to the stabilization of the system.

Abstract: Efforts to develop evaluation of networking emergency have been hampered by many obstacles. With the observation of network users’ browsing actions, the implicit feedback of the online people can be obtained based on the Web information. With the analysis of the formation of network emergency and users’ Web browsing actions, the users’ feedback information can be gotten. Based on the classification and summary of the feedback, the monitoring and evaluation index system of network emergency is set up. Furthermore, the structural model of variables effect network emergency for the emergency evaluation is established, and the empirical method for monitoring and evaluation network emergency is put forward. Empirical analysis shows that the index system and the model are reasonable. The work is of important meaning to the realization of monitoring online public security management and network emergency early warning.

Abstract: How to build the model represents the complex relationship of data and how to optimize the model has been the core issue of data mining research. BP neural network was able to characterize the nonlinear data relationships by training. But BP neural network is easy to fall into local minimum, and its hidden nodes, the connection weights and thresholds are not easy to determine. To overcome the shortcomings of the BP neural network model, this paper presents an intelligent method based on genetic algorithm optimizing the BP neural network according to the error minimization principle. Experimental results with function approximation and remote sensing image classification indicate that the optimized model can be an effective way to improve forecasting accuracy.

Abstract: The quality of decoded video in erroneous environment depends on efficient detection and concealment of errors. In this paper, an improved error detection technique and a novel temporal error concealment technique for MPEG-4 video are proposed. The proposed detection technique can detect efficiently some transmission error as well locate the exact position of the first error. The proposed temporal concealment method can mask the impairments caused by the detected error significantly with very low computation complexity. Experimental results show the improved detection technique combining with the proposed temporal concealment method can increase the video quality efficiently.

Abstract: Software measures filtration is important but often been neglected activity in software measurement. A framework for software measures filtration process that not only satisfied measurement goals but also matched organization capability is been presented. In this framework, software measures that get by GQM been evaluated on the evaluation criteria. The fuzzy mathematic expectation has been proposed to calculate measures evaluation value. The algorithm of verify goal achievable has been described. The framework ensures that measures set are most appropriate.

Abstract: The data exchange platform aims to provide an integrated, standardized and standard-complying data exchange framework for the business systems inside and outside the enterprises and solve the “information island” problem caused by differences among the application system, database, data definition and running environment. This paper designs a cross-platform, cross-system, secure and reliable data exchange platform, proposes a method for data conversion standard and implementation of isomerous data transform method and function of the integration and conversion of the isomerous data in enterprises and implements a prototype system. This data conversion technology features high efficiency, standardization, high security, openness and scalability.

Abstract: The Aircraft scheduling problem is researched in this paper, the equilibrium model of aircraft scheduling problem is proposed and a sorting algorithm is constructed. By introducing the concept of flight connections, aircraft scheduling problem is transformed into the distribution of flight connections, the mathematical model of the problem is established, to solve the model, a sorting algorithm is constructed. We use the airline's flight data to test the algorithm.The simulation results show that the model and the algorithm are feasible.

Abstract: It is important for logistics enterprise to choose the best logistics distribution route to improve efficiency. Dynamic programming is analyzed. Traffic jam factor of logistics distribution path is imported in the basic algorithm to modify the path value according to random distribution path condition. An example is used to verify the improved algorithm is practical.

Abstract: Protein structure prediction occupies an important position on bioinformatics science. In this paper, basic theory of particle swarm optimization and some theory models of protein folding study are introduced. Using modified particle swarm optimization, the protein structure prediction is predicted, and good performance of algorithm is verified by testing results of Fibonacci sequence. In the end, the future on protein structure prediction solving by particle swarm optimization is prospected.