Applied Mechanics and Materials Vols. 602-605

Abstract: The paper aims to develop an updated network system reconfigurable model based on the Finite State Automation. Firstly, the paper reviews the concept of reconfigurable network systems and reveals its robustness, evolution and the basic attributes of survivability.Then the system robust behavior, evolution behavior and survival behavior are described with a hierarchical model. Secondly, the study builds the quantitative reconfigurable metric with network topology reconfigurable measurement example. Finally, the result of experiments shows that the proposed reconfigurable quantitative indicator of reconfigurable resistance model suggests that the network is an efficient reconfigurable network topology, which can effectively adapt the dynamic changes in the environment.

Abstract: An image compression denoising method based on median filter and wavelet transform is proposed in order to overcoming shortcomings of traditional methods of image processing in this paper. This method combined hardware parallelism with software technology is enable to achieve image compression denoising and take into account algorithm validation, and fast response of the system. An real-time image processing system is design by this method. Design and hardware implementation of fast median filtering algorithm based on EP1C12 FPGA chip is realized and software simulation of median filter and wavelet transform is done. The experimental results show that this system has advantages of fast response characteristic, less time consuming and high signal to noise ratio.

Abstract: Low encoding delay and complexity is very important for image transmission. This paper proposes a novel image transmission scheme with low encoding complexity. The proposed scheme is based on quasi-cyclic low density parity check (QC-LDPC) codes with a simple recursive encoding form (SREF QC-LDPC code) which results in low encoding complexity and delay. Constructing the SREF QC-LDPC codes in this scheme composes of two main steps, construction of the base matrix and the exponent matrix. We combine the differential evolution and protograph extrinsic information transfer (PEXIT) method to optimize the base matrix of QC-LDPC code. Consequently, the exponent matrix and the parity check matrix are constructed. Simulation results show that the proposed scheme based on SREF QC-LDPC code can provide a good tradeoff between the performance and complexity.

Abstract: Given the multiple-sources feature of geological interface data, in this paper we propose a universal 3D modelling method using data forms presented as dirllhole diagrams, geologic sections, and vectorized contour maps. In our strategy, data from different sources are all treated as discrete property points, upon which cubic interpolation interpolation is performed to make a denser grid. The final step is accomplished through constrained Delaunay triangulation of the top and bottom grids and boundaries to generate the strata model through triangular strips. Our method merges all kinds of data sources available into one single modelling process, thus the most realistic result is guaranteed.

Abstract: At present, the traditional neural network model have been used in settlement prediction of buildings area, but there are some limitations. In this paper, BP neural network is applied in the settlement prediction of buildings and the prediction result is compared with the measured values. The results show that: the use of BP neural network to predict the settlement of existing buildings is feasible. The study results can provide a reference for the anti-seismic performance census of existing large area buildings.

Abstract: During animation design process, when the overlap of animation graphics is overtopping, inaccurate three-dimensional feature points appear in the established model, which resulting in low fidelity of model. For this drawbacks, a three-dimensional reality animation design modeling based on an optimization algorithm of animation modeling fidelity is proposed. Triangle refinement method is utilized to refine feature points distributed disorderly in the three-dimensional animation model, so as to obtain a three-dimensional animation composed of triangles, according to the method of calculating the intersection of intersecting triangles, optimal triangles can be achieved, i.e. the new three-dimensional coordinate points are acquired. Afterwards, two-dimensional coordinate calculation is processed for the new added points to get the exact coordinates of the point in the three-dimensional animation model, eventually obtain a three-dimensional animation model with high degree of fidelity.

Abstract: With the rapid development of engineering construction and gradual introduction of the bidding system, project cost estimation model continues to deepen. How to estimate engineering cost fast and accurately become one of the hot topics currently. In this paper, the characteristics of large-scale water project investment risk is combined to establish a neural network model suited for large-scale water project cost, through quantitating the main features of each category of water conservancy and combining neural network model established to quickly estimate water project cost with the toolbox. After engineering examples show that it is a fast and reliable water project cost estimation method.

Abstract: The communication signal attenuation compensation method for long distance communication is studied in this paper in order to improve the accuracy of the signal transmission. In long-distance communication, due to the shock pulse signal attenuation, the accuracy of signal is reduced. The use of auto-regressive integrated moving control method of error compensation can solve this problem. In the process of communication, the cumulative attenuation rate of communications network is used to establish auto-regressive integrated moving control model to achieve cumulative error compensation. The experiment results show that compensating the total amount of cumulative attenuation of signal in long-distance communication can reduce the attenuating property of communication network and achieve the requirements of communication.

Abstract: Optimization method ofmassive dataquery is researched in this paper.In the modernInternet environment,the datahas the characteristics oflarge amount of information, complexity, disorder, andchaosassociation. Using traditionalqueried methodsoftenrequirea lot oflimitedconditions, witha lot of drawbacks such as time-consuming data query, moreineffective queryand low efficiency.To this end, anoptimizationmethod of massive data query based onparallel Apriori algorithm is proposed in this paper.The massive dataare made simplification processing andredundant data are deleted to providedata foundation for fast and accuratedataquery.Effectiveassociation rulesof the massive data are calculated, in order to obtain the relevantof the target data. Based onAprioriparallel algorithm,massivedata are processedto achieveaccurate query. Experimental results show thatthe use ofoptimization algorithm for massive dataquerycan improvethe query speedof target data and it has a strong superiority.

Abstract: This paper is based on Least Squares Support Vector Machine theory to build the wind speed forecasting model. Meanwhile, as there is still no effective choice method of Least Squares Support Vector Ma-chine parameter, this paper tried to use Particle Swarm Optimization theory to optimization choice for parameter. And last, use wind farm observed wind speed (sampling interval is 1 minute) of three days to forecast the next minute wind speed through this paper's wind forecasting model, and prediction result is that the MAPE is only 4.63%, the prediction effect is relative ideal, confirm the feasibility of applying the Particle Swarm Optimization Algorithm and Least Squares Support Vector Machine theory to forecast the wind speed, it will provide theoretical support to wind farm layout and wind power forecasting and so on.