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In this paper, a modified K-means based RBFNN is discussed. To improve the performance of RBFNN, an initial cluster centers (ICCs) selection strategy is proposed for K-means algorithm. The algorithm takes breadth preferred subset of samples as ICCs to cover the sample space using greedy strategy. The results shows that the proposed algorithm can improve the performance of RBFNN remarkably in chaotic...
In K-means clustering algorithm, the selection of cluster number k and initial K-means center has certain influence on the result. It would generate very different aggregation result when confronting with some certain types of data set. This paper aims at proposing an estimation method to evaluate the initial parameters for K-means algorithm. The estimation is executed through data analysis, which...
Urban road detection with on-board monocular camera in vehicle is still a difficult problem due to its complexity. Combining the superpixel scene segmentation with the classification of texture and structure information of the road scenes, this paper explores the method of detection the road from a single image. Processing the road texture information on a large scale and the structural information...
To design an energy efficient data collection scheme instead of multi-hop data relay is essential for Wireless Sensor Networks. To many proposed data gathering approaches, the long data delay is the main problem. In this paper, mobile collectors are introduced in a sensor network and a data collection mechanism is proposed. To organize sensors into three-level clusters, an energy efficient clustering...
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