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Vegetation coverage is an important indicator for forecasting geological disasters in mountainous areas such as landslide. However, it is a challenge to extract vegetation coverage in complex terrain from SAR image. A major problem is that the variation of the backscatter coefficient of the same object varies with the local incidence angle. As a result, a large number of discrete points appear in...
The detection of ocean oil spill based on synthetic aperture radar (SAR) image has been a hot topic attracting extensive attention. In this paper, a hybrid scheme, in which we extract feature parameters and then achieve classification as follows, is presented. Two-dimensional (2-D) Otsu algorithm is applied in image segmentation process, and neural network is applied in classification course. Before...
Designing consensus function by analyzing ensemble method of clustering members and clustering, then the class center will be determined by the way of using the weighted method. Clustering ensemble, which is Based on part priority clustering algorithm, is to improve the accuracy of the algorithm. Experiments results proved that the algorithm which is optimized takes great advantages over that in scalability,...
In this paper, a method of Attribute Reduction Based on Discernibility Matrix and a proximal support vector machine (psvm) is integrated and used to implement a classification of digitized mammograms. The Attribute Reduction Algorithm is used to reduce useless and interfering attributes of medical images, and the proximal support vector machine that runs faster, and is easy to implement, is used to...
Initialization of fuzzy k-means algorithm decreases the convergent rate of clustering and leads to plenty of calculation. Thus, we propose an improved fuzzy k-means clustering based on k-center algorithm and binary tree in this paper, which firstly reduces redundant attributes while too many irrespective attributes affect the efficiency of clustering. Secondly, we remove the differences of units of...
In order to improve searching results of Web pages and enhancing Web crawling operation, the Web page clustering based on searching keywords is proposed in this paper, which firstly employed matching degree between Web pages and searching keywords to decide the sequence of showing pages of searching results. Then clustering algorithm was chosen to group pages of searching results according to matching...
The variables of organic matter, available N, available P and available K data determined in 193 topsoil (0-30 cm) samples were selected as data sources. Fuzzy c-means clustering algorithm was used to delineate management zones. In order to determine the optimum fuzzy control parameters, the fuzziness performance index (FPI), c-?? combinations and the multiple regression based on external variable...
A new method called EPDG-GA which utilizes the edge partitions dominator graph (EPDG) and genetic algorithm (GA) for branch coverage testing is presented in this paper. First, a set of critical branches (CBs) are obtained by analyzing the EPDG of the tested program, while covering all the CBs implies covering all the branches of the control flow graph (CFG). Then, the fitness functions are instrumented...
A new feature description is used for human behaviour representation and recognition. The feature is based on Radon transforms of extracted silhouettes. Key postures are selected based on the Radon transform. Key postures are combined to construct an action template for each sequence. Linear discriminant analysis (LDA) is applied to the set of key postures to obtain low dimensional feature vectors...
This paper uses data mining classification algorithms--C5.0 and CART algorithms to get useful information to decision-making out of customerspsila transaction behaviors. Firstly, by business understanding, data understanding and data preparing, modeling and evaluating we get the results of the two algorithms and by comparing the results ,we know that the two algorithms can both be applied in the customer...
Most of current anti-spam techniques, like the Bayesian anti-spam algorithm, primarily use lexical matching for filtering unsolicited bulk E-mails (UBE) and unsolicited commercial E-mails (UCE). However, precision of spam filtering is usually low when the lexical matching algorithms are used in real dynamic environments. For example, an E-mail of refrigerator advertisements is useful for most families,...
Traditional k-means algorithm can make the distances of objects in the same cluster as small as possible, but the distances of objects from different clusters are not satisfied efficiently and usually the dataset with mixed numeric and categorical data is not classified correctly. The IWEKM (improved weight entropy k-means) algorithm is proposed in this paper. The proposed algorithm overcomes the...
C4.5 is a learning algorithm that adopts local search strategy, and it cannot obtain the best decision rules. On the other hand, the simulated annealing algorithm is a globally optimized algorithm and it avoids the drawbacks of C4.5. This paper proposes a new credit evaluation method based on decision tree and simulated annealing algorithm. The experimental results demonstrate that the proposed method...
Local Binary Pattern (LBP) was designed and has been widely used for efficient texture classification. LBP provides a simple and effective way to represent texture patterns. Uniform LBPs play an important role for LBP-based pattern/object recognition as they include majority of LBPs. On the other hand, Human detection based on Mahalanobis Distance Map (MDM) recognizes appearance of human based on...
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