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In this brief paper, a simple and fast computational method, the Planar Visibility Graph Networks Algorithm was proposed based on the famous Visibility Graph Algorithm, which can fulfill converting two dimensional timeseries into a planar graph. The constructed planar graph inherits several properties of the series in its structure. Thereby, periodic series, random series, and chaotic series convert...
With the development of the mobile Internet and streaming media technology, digital music has been accepted by many people. However, in the face of the massive music data on the Internet, users want to find favorite music is like looking for a needle in a haystack via traditional music indexing techniques. In this paper, an improved algorithm for personalized music recommendation based on tag information...
In the age of Big data, it's taken more seriously for the publisher to protect the privacy information of released data. This paper focuses on the problem of Format-Preserving Encryption(FPE) of massive multi-type data and researches on the model and scheme of encryption and decryption. First of all, the model takes Excel as the unit of encryption and decryption and analyzes the file structure. Then,...
A novel method of locating all local minima of a function is presented here. Among many methods that exist in global optimization literature, Multi-start and Min-finder are effective methods because of their ability to locate not only the global minimum but also all local minima of the objective function. Both of these methods have the disadvantage of high computational cost. To remedy this, we propose...
The unstructured road detection plays a key role in an autonomous vehicle navigation system. However, the unstructured road images often contain shadows and are easily affected by ambient light, resulting to an inaccuracy with road detection. A robust road detection technique is required. In this paper, we adopted an improved fuzzy c-means(FCM) clustering algorithm to address these issues. The new...
The traditional k-mean clustering method is sensitive to the initial clustering centers and easy to fall into local optimum solution. To overcome this problem a novel kernel clustering analysis method based on an almost parameter-free evolutionary algorithm, bare bones differential evolution (BBDE), is proposed in this paper. The constituent elements of the proposed method and its general steps to...
The Embarrassingly Parallel (EP) algorithm which is typical of many Monte Carlo applications provides an estimate of the upper achievable limits for double precision performance of parallel supercomputers. Recently, Intel released Many Integrated Core (MIC) architecture as a many-core co-processor. MIC often offers more than 50 cores each of which can run four hardware threads as well as 512-bit vector...
A Waste Collection Arc Vehicle Routing Problem with turn constraints (WCAVRPTC) model is proposed to minimize the length of municipal solid waste (MSW) collection routes, which presents several characteristics derived from traffic regulations: some streets can be traversed crossed in only one direction, and some turns should be forbidden when the common angle is too narrow. The problem is transformed...
The waste collection vehicle routing problems with time windows and intermediate facilities (WCVRPTW-IF) is actually belong to a well-known generalization of VRP, the Multi-Depot Vehicle Routing Problem with Inter-Depot Routes (MDVRPI), which is a combinatorial optimization problem and holds a central place in reverse logistics management. in order to improve the route compactness, which is very important...
This paper proposes a hybrid algorithm based on improved LLE and adaptive k-means for visual codebook generation in tourism scene classification. Firstly, we construct the improved LLE algorithm to get lower dimensional and compressed image feature representations. Then we form the adaptive k-means clustering algorithm to generate the visual codebook. Finally, we use the visual codebook histogram...
It has been a challenge to locate character in flash due to the variations of character in size, color and style. Besides, multilingual text in flash brings more difficulties to character localization. In this paper, a novel character localization method based on connected component analysis is proposed for locating character in flash. The proposed method first clusters the color to separate the color...
Outlier detection is a hot topic of data mining. After analyzing current detection technologies, a detection method of outlier based on clustering analysis is proposed, in which an effective sample is screened out from original data. According to agglomerative of hierarchical clustering, credible sample set is found. Then mathematical expectation and standard deviation are obtained by credible sample...
Wireless sensor network is composed of hundreds of sensor nodes involving in limited energy, efficient and low-energy consuming routing algorithm is the crucial problem to the routing design. In this paper, the LEACH protocol, which is a typical clustering routing protocol, has been researched and improved based on energy, the new algorithm is different from the LEACH in the method of determining...
Outlier detection is a hot topic of data mining. After studying the existing classical algorithms of detecting outliers, this paper proposes an outlier mining algorithm based on probability, and makes a new definition for outlier. It clusterings firstly with density-based algorithm, and determines suspicious outlier. Then, outlier will be detected according to probability. The experiment results on...
Recently, the sizes of networks are always very huge, and they take on distributed nature. Aiming at this kind of network clustering problem, in the sight of local view, this paper proposes a fast network clustering algorithm in which each node is regarded as an agent, and each agent tries to maximize its local function in order to optimize network modularity defined by function Q, rather than optimize...
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