Advanced Materials Research Vols. 989-994

Abstract: With the establishment of large-scale real estate enterprises, the competition is increasing among real estate enterprises, which requires real estate companies to enhance crisis prevention awareness. In the paper a combination of qualitative and quantitative method is used aiming at certain risks that real estate enterprises are facing with. The article introduces the capacity of external financing in time, Eva, cash flow, board size, the scale of supervisor board and other new indicators to establish a new system of early warning indicators. The article provides empirical study from the perspective of early warning system of real estate generation enterprise using comprehensive evaluation model. It is more accurate to predict financial risk for real estate enterprises based on the qualitative method with quantitative method.

Abstract: The aerosol fire extinguishing agent is a complex pyrotechnic composition, and the extinguishing efficiency need a series of experiments to identify. A method is put forward out based on combining back-propagation neural network and genetic algorithm (BP-GA) in this paper, and then the performance of aerosol fire extinguishing agent can be predicted in advance by the formulation. In the method, back-propagation (BP) algorithm was proposed to map the complex relationship between additive components and quality indexes of formulation. The genetic algorithm was employed to optimize the BP neural network weight and threshold. The results showed that the prediction display a satisfied consistence with the test and the error is less than 5%, and also indicated that the combining BP-GA method was an effective tool to predict the performance of aerosol fire extinguishing agent by the formulation designed.

Abstract: This paper is devoted to the study of the algebraic structure of one-Lee weight codes over. We first give some necessary conditions for a code to be a one-Lee weight code over. Moreover, we present the method of the construction of one-Lee weight codes over. An example is given to illustrate the results.

Abstract: In order to research dynamic network astringency reaching uniformity, this paper perfects the Vicsek model and puts forward improving dynamic network astringency efficiency by weighted model. We prove that the convergence rate of weighted model is faster than the classic Vicsek model and it can optimize dynamic network.

Abstract: Graph is Laplacian integral, if all the eigenvalues of its Laplacian matrix are integral. In this paper, we obtain that the Laplacian characteristic polynomials of graphs by calculation. Characterizes the new class of Laplacian integral graphs .

Abstract: To solve the crosstalk noise question in deep-submicron technologies, an efficient methodology for estimating interconnect crosstalk noise is proposed in this paper. PCA and ICA techniques are applied to reduce correlations of process variations, and moment matching scheme is used to obtain the PDF of crosstalk noise in victim coupled with multiple aggressors. Experimental results show that our method maintains the efficiency of past approaches, and significantly improves on their accuracy.

Abstract: In this paper, a novel feature-based real-time visual Simultaneous localization and mapping (SLAM) system is proposed. This system generates colored 3-D reconstruction models and 3-D estimated trajectory using a Kinect style camera. Microsoft Kinect, a low priced 3-D camera, is the only sensor we use in our experiment. Kinect style sensors give RGB-D (red-green-blue depth) data which contains 2D image and per-pixel depth information. ORB (Oriented FAST and Rotated BRIEF) is the algorithm used to extract image features for speed up the whole system. Our system can be used to generate 3-D detailed reconstruction models. Furthermore, an estimated 3D trajectory of the sensor is given in this paper. The results of the experiments demonstrate that our system performs robustly and effectively in both getting detailed 3D models and mapping camera trajectory.

Abstract: The topology relation is the important basis of GIS data modeling, spatial query, spatial analysis, spatial reasoning and so on. This paper summarizes the current research progress of topological relations between complicated objects (with holes). In accordance with the order of the number of holes, respectively introduce D9-intersection model, 4-4ID model, HFM model and so on, and then analyzes their presentation skills, advantages and defects, so as to provide reference for subsequent research.

Abstract: Weight function neural network is a new kind of neural network developed in recent years, which has many advantages, such as finding globe minima directly, good performance of generalization, extracting some useful information inherent in the problems and so on. Time complexity is an important measure of algorithm. This paper studies the complexity of neural network using second class orthogonal weight functions. The results indicate that the neural network has a linear relationship with the dimensions of input layer and output layer, an O (n³) relationship with the number of samples. Finally gives some simulation experiments for time complexity.

Abstract: Traditional algorithms of training neural networks have some weakness. A new approach using weight function neural networks was proposed in recent years, which overcomes the shortcomings of traditional neural networks. This paper takes Padé approximation as weight functions and we get the method of how to find the Padé weight functions with given samples. Then complexity is also analysed in detailed in this paper. Finally simulation experiments are done to verify the results.