Advanced Materials Research Vols. 926-930

Abstract: That applying computer vision technology into the water surface floater intelligent monitoring is a creative and interesting topic. In this article, we propose the water surface floater clustering based on Mean Shift algorithm. Adopting RGB space color information, the image is divided into fixed size 3*3 small blocks, the block is mapped as vertex of graph, and each block pixel mean is mapped as pixel values of vertex; before using the Mean Shift clustering put forward carrying on one or more Mean Shift filtering smoothing process. Finally, each vertex of clustering is mapped to a 3*3 small blocks, block pixel values are vertex pixel values, and according to the proportion of all kinds of floater in the perceptual area, calculate its pollution degree, it is used to measure or evaluate the pollution index of water surface. It is showed that the method is effective and feasible by experiment.

Abstract: Chaos is a non-linear phenomenon that widely exists in the nature. Due to the ease of implementation and its special ability to avoid being trapped in local optima, chaos has been a novel optimization technique and chaos-based searching algorithms have aroused intense interests. Many real world optimization problems are dynamic in which global optimum and local optima change over time. Particle swarm optimization has performed well to find and track optima in static environments. When the particle swarm optimization (PSO) algorithm is used in dynamic multi-objective problems, there exist some problems, such as easily falling into prematurely, having slow convergence rate and so on. To solve above problems, a hybrid PSO algorithm based on chaos algorithm is brought forward. The hybrid PSO algorithm not only has the efficient parallelism but also increases the diversity of population because of the chaos algorithm. The simulation result shows that the new algorithm is prior to traditional PSO algorithm, having stronger adaptability and convergence, solving better the question on moving peaks benchmark.

Abstract: In order to meet the trend and consumer demands for video information, the ISO/IEC group and ITU-T video encoding expert group have cooperated in making the new video encoding standard of HEVC. It defines 35 Intra prediction modes and thus has a very high encoding complexity. In order to reduce this complexity, this paper has proposed a new algorithm to effectively reduce the number of the candidate mode which needs to be checked. The edge detection and Hough transform are utilized for the prediction unit (PU) with different sizes. Statistical analysis is utilized for the detected edge line angles to decide the candidate modes that need to be checked. The C++ and OpenCV language have been utilized for the implementation of the proposed algorithm. The proposed algorithm can reduce the encoding time by 43.72 percent at most and 17.06 percent at least with just little increase of the code rate and small decrease of the PSNR.

Abstract: We herein present a satisfaction differential evolution algorithm to deal with machine layout in assembly plant. This paper firstly provide the assumption for detailed machine layout problem, build a mathematical model of detailed machine layout, and replace the optimal solution with satisfactory solution, combine satisfactory optimization theory with differential evolution algorithms, employ satisfaction function as the objective function of differential evolution algorithm. The experimental results verified our methods with practical engineering examples.

Abstract: This paper proposes a text localization method with multi-features based on cascade classifier for a variety of web images. Specifically, first, the original image is divided into sub-images with different scales, which form more satisfactory edge image blocks after being pretreated respectively; then, the researchers determine in the classifier whether the text area is contained in the candidate image blocks according to the edge connectivity characteristics, stroke density characteristics and text arrangement characteristics of text area; finally, the location results of sub-images with different scales are mixed together to obtain the final result. The experiments show that this location method has the relatively high precision and recall rate and quite strong robustness, which is suitable for a variety of web images.

Abstract: Multi-depot vehicle routing problem (MDVRP for short) is complex and a typical NP-Hard problem in manufactories, especially in assembly plant. We herein present an ant colony algorithm with memory grouping list (ACMGL for short) to solve this problem. To handle affiliation between clients and depots, we present certain point grouping (CP Grouping) and uncertain point grouping (UP Grouping) and obtain variable grouping purposes, make a grouping memory list for each depot store the optimal value and path of uncertain grouping after UP grouping, and thus improve the efficiency of the operation. Experimental results verified our algorithm in the computational efficiency.

Abstract: In this paper, the economic planning was conducted for the application of game theory in multi-objective area. The study and combined application of fuzzy comprehensive evaluation and analytical hierarchy process were also performed. On this basis, a portfolio selection model based on fuzzy comprehensive evaluation was designed and its application was simulated.

Abstract: This paper has researched traditional algorithms. The defects had been pointed out and proved. According to this, setup calculation algorithm was optimized. Considering strip transverse flow and creep deformation, natural output profile was defined. Practical applications in domestic 1500 hot strip mill show that the setup calculation strategy achieved good effect and enhanced the profile and flatness precision

Abstract: Bidirectional maximum matching algorithm (BMM) combined positive maximal matching and reverse maximal matching algorithm, it was a more commonly used word segmentation method now, but it was low efficient and couldn’t solve the ambiguity. Therefore, an improved method was proposed combining with improved dictionary structure, and changing maximal matching word length dynamically to improve the efficiency of word segmentation. In order to get the correct segmentation results, we also proposed several rules. Compared with traditional segmentation methods, it proves that bidirectional maximal matching word segmentation with rules has higher speed and precision.

Abstract: Aiming at the problem of capsule defect species diversity and classification difficulty in the process of actual capsule defect detection, this paper extracts capsule defect feature based on capsule texture, shape and capsule defect region by edge detector, and then applies hierarchical SVMs multi-class classification to classifying. In order to resolve the problems of training data imbalance and the hierarchical SVM error accumulation, a algorithm of constructing hierarchical structure is proposed that takes the principle of dividing all sample data into two more imbalanced categories according to the length of training data, and then considering significant degree of capsule defect and the probability level of capsule defect occurrence. The experimental results show that compared with the method of BP neural network, the hierarchical SVMs achieved a better classification result.