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In traditional grid clustering algorithms, the cluster results are just consisted of dense grids so that the clustering quality is low, while these algorithms are unable to cluster the multi-density datasets. In this paper, we propose a clustering algorithm based on grid and boundary over multi-density datasets. In order to describe the data distribution, boundary grid is introduced and checked by...
This paper aims to develop a decision rule-based model of household car ownership by using household travel survey data. The rough set approach as one of data mining techniques provides an effective tool to model the presented data set with decision rule sets. In this paper, the outputted “if-then” rules show the significant relationships between car ownership type and household characteristics. The...
Half duplex devices are widely used in today's wireless networks. These devices can only send or receive, but not do both at the same time. In this paper, we use cooperative decode-forward relay strategies to increase the throughput of half-duplex wireless networks. Due to the half duplex constraint, relays need to carefully choose their transmission states in order to maximize the throughput. We...
Let Delta be an arbitrary regular triangulation of a simply connected domain and I1Delta be a restrictive appointed point triangulation related to A. In this paper, employing the well-known Bezier-net method, we study the algebraic structure of bivariate C1 quadratic weak spline space W21(I1Delta).
By analyzing the topological relationships between network elements, this paper extends a turn-based algorithm for the network loading of logit type, which has a structure similar to Dial's algorithm. Based on the conservation of flows on links, the algorithm computes directly the link flow and turn flow pattern that not only agrees with the logit path-choice process but also takes into account the...
This paper analyses the advantages and disadvantages of the K-means algorithm and the DENCLUE algorithm. In order to realise the automation of clustering analysis and eliminate human factors, both partitioning and density-based methods were adopted, resulting in a new algorithm - Clustering Algorithm based on object Density and Direction (CADD). This paper discusses the theory and algorithm design...
Association analysis arises in many important applications such as bioinformatics and business intelligence. Given a large collection of measurements over a set of samples, association analysis aims to find dependencies of target variables to subsets of measurements. Most previous algorithms adopt a two-stage approach; they first group samples based on the similarity in the subset of measurements,...
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