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To measure the performance or validity of clustering algorithms, several evaluation values, such as successful rate, successful number and full successful rate are defined. In order to ensure each cluster to at least contain one vector data, and to maximize several proposed evaluation values, two class assignment algorithms are designed. To testify their performance, we employ them to the k-means...
This paper investigates the problem of acquiring planar object maps of indoor household environments in particular kitchens. The objects modeled in these maps include tables, walls and ceilings. Our segmentation approach is based on 3D point cloud data representations. In order to solve the segmentation problem in complicated environment, a variable model is used in this paper. It is applied in 3D...
In order to efficiently recognize the partially ordered or interleaved, multiple plans, treat the partial observability of the domains and exclude misleading actions, in this paper, we designed a new plan recognition algorithm based on extending and pruning the Explanation Graph and then implemented it using the VC++ programming language. The results of test experiment indicate that the algorithm...
Feature selection only using wrapper method in high-dimensional data space is always time-consuming. A new feature selection method, named fast static particle swarm optimization, is proposed for tackling this problem. It treats the whole initial feature set as a static particle swarm in which no new particle would be generated in high dimensional space, and the proposed method takes filter and wrapper...
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