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With the wide application of GIS to all kinds of fields, and developing of the technique of data mining and spatial data collection, the technique of data mining in spatial database-spatial data mining is coming out. In order to satisfy the people's demand for the interesting and potentially useful knowledge from the spatial database, this thesis used a wide using spatial clustering algorithm: k-means...
As K-means Clustering Algorithm is sensitive to the choice of the initial cluster centers and it is difficult to determine the cluster number and it is easy to be impacted by isolated points, propose the K-means multiple Clustering Method Based on Pseudo Parallel Genetic Algorithm. In the method, adopt the strategy of Variable-Length Chromosome real-coded. Through the introduction of chromosome retreading...
In this paper, an improved Differential Evolution algorithm (ACDE-O) with cluster number oscillation for automatic crisp clustering has been presented. The proposed algorithm needs no prior knowledge of the number of clusters of the data. Rather, it finds the optimal number of clusters on the processing with stable and fast convergence, cluster number oscillation mechanism will search more possible...
Aircraft-sequencing problem (ASP) is a major issue in air traffic control operations and it is also an NP-hard problem with large-scale and multi-constraint, thus it is hard to find optimal solution efficiently. This paper proposes a hybrid algorithm by means of integrating bee evolutionary genetic algorithm with modified clustering method (named BEGA-CM) for solving ASP. In details, clustering method...
Fuzzy K-prototypes is a very efficient algorithm for processing large scale mixed data set, but the selection of initial clustering center has an important impact on the clustering effect of algorithm. FKP algorithm is improved by using genetic algorithm in this paper. Seeking the initial clustering center for fuzzy K-prototypes algorithm by using genetic algorithm overcomes the shortcoming effectively,...
Distributed clustering is a new research field of data mining now. In this paper, one of distributed clustering named DCBKC (distributed clustering based on K-means and coarse-grained parallel genetic algorithm) based on K-means and coarse-grained parallel genetic algorithm is advanced. The algorithm can solve local clustering problem of distributed clustering effectively, reflect all of local data...
Image segmentation is the key step from image processing to image analysis. Ostu thresholding, which features a good performance, is one of the main image threshold segmentation methods. Like other threshold methods, the application of the Otsu has been restricted for the long-paying computation. In order to overcome the disadvantages and get better results, a new method based on quantum particle...
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