Advanced Materials Research Vols. 1049-1050

Abstract: In order to efficiently solve the routing optimization problem of logistics distribution vehicle, a new chaotic cuckoo optimization algorithm have been put forward, first, the algorithm is used for seeking optimization, chaotic perturbation operator is added in the parasitic nest position in the iteration, thereby the population diversity is expanded and the algorithm accuracy is improved. The simulation experiment is carried out for this algorithm; the result shows that the algorithm is to seek the optimal solution, the average solution, and find the optimal solution frequency and time, which all has obvious effects.

Abstract: When the background is complex and there is a lot color similar pixel interference, it may lead to location and size of Camshift algorithm’s search window abnormal so as to tracking failure. Aiming at these problems, this paper proposed a algorithm that combinating Camshift algorithm and Kalman filter. Kalman filter can predict the position of the moving object. Camshift algorithm adjusted the position and size of search window by using the prediction, so as to ensure the correct operation of the Camshift algorithm. Experimental results show that the proposed algorithm can effectively overcome the large area of similar color background and occlusion and many colors similar moving targets interference and other issues, improve the accuracy and robustness of target tracking algorithm.

Abstract: The traditional evolutionary algorithm is cannot converge faster to solve the path optimization problems, and the path that is computed is not the shortest path, in allusion to the disadvantage of this algorithm, a mutation particle swarm optimization algorithm is proposed. The algorithm introduces the adaptive mutation strategy, and accelerated the speed to search for the global optimal solution. For seven examples experiment in standard database, the result shows that the algorithm is more efficient..

Abstract: The Hilbert-Huang Transform (HHT) is a new time-frequency analysis with adaptability and orthogonality, but it is rather weak in terms of noise resistance, even low noise can disturb the HHT result greatly. The paper launches an investigation on how noises affect the HHT result and proposes the method to solve the problem. The analytic framework for HHT is first introduced, the feature of the test signal is extracted by HHT. Median filter is adopted to reduce the frequency leakage of certain signal component caused by white noise. The method proposed is experimentally simulated and the results demonstrate its effectiveness.

Abstract: Accurate evaluation of image quality is always being a problem. With blurry cotton images as samples, using variance methods, average gradient method, gray prediction error statistics method and information entropy method, this research evaluated restoration quality of 4 kinds of images from the perspective of grayscale contrast, sharpness, contrast and ambiguity. The results show that the 4 image restoration algorithms all improved image quality, and Wiener algorithm improved image quality best comparing with other 3 algorithms, Reg second, Blind algorithm and K-L algorithm were worse.

Abstract: In view of the higher mistaken-detection rate problem of the human face detection in complex conditions, we put forward an improved algorithm. This article Proposes one kind of the method Which unifies the level of difference between the threshold and the feature value of the weak classifier with the weak classifier's overall error rate. Compared to the method which only based on the overall classification error rate to update the weights, this method can achieve higher detection rate while reduces the mistaken-detection rate. This article redefines the training error which is caused When we train the weak classifier, and Proposes MCE-AdaBoost algorithm. The new definition of training error will pay more attention to the error Which erroneously estimates the face Sample as non-face sample; this much more conforms to face detection of this special target detection issue. The experimental results show that MCE-AdaBoost algorithm can effectively improve the detection Performance of the final classifier.

Abstract: The horizontal curve is a very common linear in the road design. On the other hand, the horizontal curve in the approach bridge may affect the traffic flow in many ways. The north approach span of Nanjing Yangtze River Bridge is herein taken as an example. With the help of the traffic speed data ,traffic density data and traffic volume data from the traffic survey and analysis, the features of traffic flow,which change with the morning peak appearing, have been found by modeling. Finally, the paper gives several ways to optimize the traffic management and control, improve transport and security.

Abstract: In this paper, we improved the traditional FF (floor Field) model by using the theory of cellular automata on personnel evacuation simulation on redefining static and dynamic field strength and adding guide field strength in the model. The extended model analyzed the different impact of directional dynamic guiding mode on personnel evacuation behavior and after the simulation of an evacuation in an imaginary supermarket, the analysis of the situation shows a better result.

Abstract: Pulse compression technology is one of the key technologies in the field of modern radar signal processing, can effectively solve the contradiction between action distance and resolution. In this paper, a radar digital pulse compression system is designed and implemented based on FPGA with linear frequency modulated signal. The digital pulse compression module is designed using FFT IP core which can be reused in different periods of DPC, respectively performing FFT and IFFT calculation, so that the hardware consumption is saved significantly. Therefore, compared with other systems, the system designed in this paper has the characters of fast processing speed, high degree of modularity, real-time processing and short development cycle.

Abstract: Anti-collision algorithms for active RFID system which are based on the ALOHA always have a serious overhearing problem because of the random selection in the system. Although the active tag can avoid the overhearing problem to some extent by applying the tree-based deterministic anti-collision algorithm, the system will using more time on account of more reader queries. We propose a novel algorithm which based on the superiorities in the recalled protocols. Simulation results show that the algorithm effectively reduce excessive inventory listening and system delay.