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The multidepot vehicle routing problem with interdepot routes (MDVRPI) is an extension to the classical vehicle routing problem (VRP); it is the major research topics in the supply chain management field. It is an extension of the multidepot vehicle routing problem in which vehicles may be replenished at intermediate depots along their route. In this paper, we propose a heuristic combining the adaptative...
Image representation is an important issue in computer graphics, computer vision, robotics, image processing and pattern recognition. In this paper, we proposed an improved color image representation method by using the direct non-symmetry and anti-packing model with triangles and rectangles (DNAMTR). Also, we propose an algorithm of the DNAMTR for color images and analyze the total data amount of...
Neural network is a technology for intelligent transportation system and it is important in vehicle type recognition. However, traditional vehicle type recognition method always utilize BP network. A new vehicle type recognition based on radial basic function neural network was proposed. Also discussed are the problem of feature of vehicle feature vector, the problem of normalization of the image-size,...
Vehicle type recognition is an active subject in the area of computer pattern recognition, which has been a focus in reach for the last couple of decades because of its wide potential application. And edge detection is an important step for vehicle type recognition, a vehicle type recognition method based on Sobel was proposed. Also discussed are the vehicle vector and the vehicle recognize process...
Vehicle type automatic recognition is of great important today in intelligent transportation system. And neural network is often applied to recognize the vehicle type. However, the network can be very complex and therefore difficult to be trained. In order to cope with such issues, a new developed vehicle type recognition method based on contour feature is presented in this study. It is applied to...
This system is modeled on the distance perception methods of human eyes. It uses DSP to process the images obtained by two CCD cameras and calculate the distance by the principle of parallax. This paper describes the working principle and hardware platform design. It focuses on the image matching methods based on Canny edge detection and Harris corner detection. The results of the experiment show...
The traditional three-dimensional object recognition method based on hypothesise and test need to solve the coordinate transformation matrix from scene to model through a group of non-linear equations. Therefore, it has a very high complexity. This paper presents a man-made object recognition method based on the geometry feature of line segments characteristics, and disperses the overall coordinate...
Active appearance models are widely used to match statistical models of shape and appearance to new images rapidly. They work by finding model parameters which minimise the sum of squares of residual differences between model and target image. A limitation of AAMs is that they are not robust to a large set of gross outliers. Using a robust kernel can help, but there are potential problems in determining...
In this paper, an algorithm using point feature and intensity feature combined with the Artificial Immune algorithm is presented. First, the feature points of the two images are extracted by Harris corner detector to reduce the amount of computation. Then, the mutual information (MI) is used to be the similarity measure for MI algorithm based on intensity has excellent robustness and accuracy. Finally,...
In this paper, we present an effective feature normalization algorithm to improve the robustness of automatic speech recognition systems. At front-end, minimum mean square error log-spectral amplitude estimation speech enhancement is adopted to suppress noise from noisy speech. Then, at back-end, the histogram equalization feature normalization is used to deal with the residual mismatch between enhanced...
Although the image representation methods of the hierarchical data structures have many merits and applications, they put too much emphasis upon the symmetry of segmentation. Therefore, they are not the optimal representation methods. In this paper, we propose a novel gray image representation method by using the direct non-symmetry and anti-packing model with K-lines (DNAMK). Also, we present an...
By analyzing the characters of CT medical image, this paper proposes a novel method for this particular image fusion, which is using discrete wavelet transform and independent component analysis. Firstly, each of CT images were decomposed by 2-D discrete wavelet transform. Then independent component analysis were used to analyse the wavelet coefficients in different level for acquiring independent...
A prediction model-based fuzzy neural network (PFNN) approach is proposed, in which a basic FNN is created at first to predict the relative position of the trajectory. Then a FNN is used independently to get the control values of the variables for motor motion according to those variables including trajectory position both from those measured and predicted values, and those speed variables. At last...
This paper deals with the problem of recognizing textures in images. For this purpose we employ a technique based on the fractal dimension (FD) and a new fractal dimension estimating method is proposed by taking the area instead of the volume covering in box-counting to estimate the FD. Three FD features are based on the original image, the above average/high gray level image, the below average/low...
The traditional group decision-making method mostly is static aggregation method which scientifically defines the decision weighted vector of each decision makers. In fact, the group decision making convergence is always a dynamic process. The preferences of decision maker are dynamic changing in this process, it is more realistic to apply the dynamic model to consider the consistence convergence...
With the development and advancement of reverse logistics concepts and practice, the evaluation and selection of vendors or partners for the specific function of reverse logistics support becomes more important. This paper firstly analyses the framework of selecting a third-party reverse logistics provider. Next, this paper presents a set of evaluation index system for choosing a third-party reverse...
A novel gene regulatory network model via the fuzzy logic is proposed. Fuzzy logic can effectively model gene regulation and interaction to accurately reflect the underlying biology. By judging genes expression level on the fuzzy rule, Fuzzy Boolean network (FBN) makes it possible to handle simultaneously the randomness and fuzziness of biological phenomena.
The aim of this paper is to solve the portfolio problem when security returns are bifuzzy variables. Two types of portfolio selections based on chance measure are provided according to bifuzzy theory. Since the proposed optimization problems are difficult to solve by traditional methods, A hybrid intelligent algorithm by integrating bifuzzy simulation and genetic algorithm is designed. Finally, one...
This paper proposes a strategy of query optimization based on domain ontology. Three kinds of query optimization respectively based on is-a relation, part-of relation, and equivalent-class relation in the domain ontology are investigated. By using this strategy, a domain-specific information searching system building upon GoogleAPI and domain ontology is built, where optimized user query is processed...
First, the background, significance and general implementation of vehicle license plate recognition (VLPR) are introduced. Based on analyzing the theory of neural network pattern recognition system, toward the limitation of standard BP, this thesis offers its improved method and a real recognition example. Finally, conclusion on its characteristic is given. The improved BP algorithm had some advantages...
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