Advanced Materials Research Vols. 926-930

Abstract: The spatial data of mine is analyzed and processed in this study. This research mainly include: calculate 3d coordinate of points of drill hole axis, calculate 3d coordinates of drill hole axis and stratum surface, insert virtual drill hole and calculate it's ostiole 3d coordinate, divide and number stratum of study area. Finally, this research design drill hole database and realize storage and management of mine geological data. This study also researched the classification and characteristics of 3d spatial data model. Based on distribution characteristics of mine data and application purpose of 3d model, this paper choose quasi tri-prism as basic volume to build 3d geological model. The improvement of data structure and modeling algorithm of quasi tri-prism make it can better adapt to the complex geological body modeling. This research study the expansion rule of triangle, modeling algorithm of quasi tri-prism and finally design geologic body database and realize storage and management of geological modeling data.

Abstract: The semi-parametric estimation method includes not only a parametric component, but also a nonparametric component. The two-stage estimation method is analyzed in this study and the final estimation of variables is also given. The method is used to predict the data of temperature monitoring of a certain area and the result shows that the semi-parametric model takes into account of the influence of systematic error, the prediction is preferable. The semi-parametric estimation is well applied in temperature monitoring forecast and some other actual problems.

Abstract: BP neural network has excellent ability to solve nonlinear optimal problem for its powerful simulation calculation ability and is wildly used in various disciplines in recent years, but its shortages of low convergence speed and falling into local minimum easily limit the usage of the algorithm. Based on the Levenberg-Marqardt optimization algorithm, the paper improves the BP neural network to overcome its shortages. First, the working structure and shortages of BP neural network are analyzed with more details. Second, the working principle of BP neural network algorithm is improved with Levenberg-Marqardt optimization algorithm and the calculation flows is redesigned. Third, data from three universities are used to realize the improved algorithm and the experimental results shows that the improved BP algorithm has better performance in calculation time and evaluation accuracy when used in university classroom teaching evaluation practically.

Abstract: When a security attribute of the assets assignment is valuated, the commonly used method is based on the analysis of the corporate business strategy, combined with the data value given directly by the experience and intuition of the evaluators. This assessment process is lack of scientific basis. Grey Statistical evaluation can composite the views of related personnel in different department and give confidence interval. The scientific, objective and impartial assignment process is ensured by the statistical results. For example of asset integrity assignment, the process can be completed by the method used of grey statistical evaluation.

Abstract: The generation flow of three-dimensional (3-D) process model used for complex parts is the key in the 3-D process technology. The technology of 3-D process model generation flow is talked about, including the definition of 3-D process model, information acquisition of manufacturing feature and process information, etc. The key characteristics of 3-D process technology that the matching manufacturing feature with process information and 3-D process scheme analysis are researched. At last, reversely suppression of manufacturing feature is used for solving the generation of 3-D process model.

Abstract: The article provides an overview of integration in the field of Internet technology and its trend, combined with the successful application of intelligent transportation system case system provides next - generation model of intelligent transportation system based on Internet of Things, details the functions and features of each subsystem, a case study of typical traffic guidance applications, describes the model and key technology of the Internet of its implementation.

Abstract: As the growing demand for cloud computing, the scale of cloud data centers increased gradually, so that the energy issues of cloud environments have become increasingly prominent. For the situation of energy consumption serious in cloud computing data center, the resource scheduling algorithm of cloud computing for energy optimization was designed base on the technology of virtual machine migration. The energy consumption of cloud data center was saved effectively through effective use of resources, rational allocation of resources scheduling. Simulation results showed that compared to sequence execution algorithm, utilization of CPU, the average energy consumption, the average time was reduced by 16.63%, 27.26% and 23.72%, respectively.

Abstract: The cloud computing task scheduling field representative algorithms was introduced and analyzed : genetic algorithm, particle swarm optimization, ant colony algorithm. Parallelism and global search solution space is the characteristic of genetic algorithm, genetic iterations difficult to proceed when genetic individuals are very similar; Particle swarm optimization in the initial stage is fast, slow convergence speed in the later stage ; Ant colony algorithm optimization ability is good, slow convergence speed in its first stage; Finally, the summary and prospect the future research direction.

Abstract: The traveling wave solutions to the heigher order Korteweg-de Vries equation is obtained by using Riccati equation. The method is straightforward and concise, the applications are promising to obtain traveling wave solutions of various partial differential equations. It is shown that the Riccati equation method, with the symbolic computation, provide an effective and powerful mathematical tools for solving such systems. The numerical simulation of the solutions are given for completeness.

Abstract: DEC-POMDP(Distributed Partially Observable Markov Decision Process) model is a multi-agent model of collaborative decision-making is important, but due to an alarming number of DEC-POMDP problem state space and great strategy solution space, so DEC-POMDP solution of the problem becomes very difficult. The agent from the initial state to the target state during the interaction with the environment, the system's maximum benefit is often only with some small amount of a higher reward states. This article by searching from the initial belief state to the target state to get a shortest Hamiltonian path, according to the corresponding sequence of actions on the path forward search to get faith belief state space trajectory, and then along the trajectory reverse convictions value function iteration, thus forming the state with the largest gains beliefs trajectory corresponding optimal strategy. In this paper, shortest Hamiltonian path-based value iteration to search the optimal path of faith so as to solve the state Hamiltonian larger DEC-POMDP problem.