A procedure for optimal design of District Metered Areas (DMAs) within a water distribution network based on a multilevel balancing and refinement algorithm to partition the network and determine the optimal meter pos...
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A procedure for optimal design of District Metered Areas (DMAs) within a water distribution network based on a multilevel balancing and refinement algorithm to partition the network and determine the optimal meter positions, coupled with a pressure driven hydraulic simulator to quantify the hydraulic performance of the districtualized system, is presented. Unlike other procedures based on graph partitioning techniques proposed in the scientific literature, the two main issues involved in the design of the DMAs, namely a) how to partition the nodes into the required number of districts, and b) which pipes linking districts to leave open, and fitted with an assigned number of flow meters, and which to close, are simultaneously resolved. The application of this procedure to a real case shows that this approach provides design solutions well adapted to different numbers of measuring points, yielding superior performance indicator values to similar procedures reported in the literature and used here for comparative purposes.
A novel RSSI (Received Signal Strength Indication) refinement algorithm is proposed to enhance the resolution for indoor and outdoor real-time location tracking system. The proposed refinement algorithm is implemented...
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A novel RSSI (Received Signal Strength Indication) refinement algorithm is proposed to enhance the resolution for indoor and outdoor real-time location tracking system. The proposed refinement algorithm is implemented in two separate phases. During the first phase, called the pre-processing step, RSSI values at different static locations are collected and processed to build a calibrated model for each reference node. Different measurement campaigns pertinent to each parameter in the model are implemented to analyze the sensitivity of RSSI. The propagation models constructed for each reference nodes are needed by the second phase. During the next phase, called the runtime process, real-time tracking is performed. Smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the mobile target is moving. Filtered RSSI values are converted to distances using formula calibrated in the first phase. Finally, an iterative trilateration algorithm is used for position estimation. Experiments relevant to the optimization algorithm are carried out in both indoor and outdoor environments and the results validated the feasibility of proposed algorithm in reducing the dynamic fluctuation for more accurate position estimation.
The original k-means clustering algorithm is designed to work primarily on numeric data sets. This prohibits the algorithm from being directly applied to categorical data clustering in many data mining applications. T...
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The original k-means clustering algorithm is designed to work primarily on numeric data sets. This prohibits the algorithm from being directly applied to categorical data clustering in many data mining applications. The k-modes algorithm [Z. Huang, Clustering large data sets with mixed numeric and categorical value, in: Proceedings of the First Pacific Asia Knowledge Discovery and Data Mining Conference. World Scientific, Singapore, 1997, pp. 21-34] extended the k-means paradigm to cluster categorical data by using a frequency-based method to update the cluster modes versus the k-means fashion of minimizing a numerically valued cost. However, as is the case with most data clustering algorithms, the algorithm requires a pre-setting or random selection of initial points (modes) of the clusters. The differences on the initial points often lead to considerable distinct cluster results. In this paper we present an experimental study on applying Bradley and Fayyad's iterative initial-point refinement algorithm to the k-modes clustering to improve the accurate and repetitiveness of the clustering results [cf. P. Bradley, U. Fayyad, Refining initial points for k-mean clustering, in: Proceedings of the 15th International Conference on Machine Learning, Morgan Kaufmann, Los Altos, CA, 1998]. Experiments show that the k-modes clustering algorithm using refined initial points leads to higher precision results much more reliably than the random selection method without refinement, thus making the refinement process applicable to many data mining applications with categorical data. (C) 2002 Elsevier Science B.V. All rights reserved.
To construct a high efficient text clustering algorithm the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of ...
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To construct a high efficient text clustering algorithm the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of clustering algorithm has to be improved with the refinement algorithm application. The experiment result demonstrated that the multilevel graph text clustering algorithm is available.
Key words text clustering - multilevel coarsen graph model - refinement algorithm - high-dimensional clustering
CLC number TP301
Foundation item: Supported by the National Natural Science Foundation of China (60173051)
Biography: CHEN Jian-bin(1970-), male, Associate professor, Ph. D., research direction: data mining.
The formal description of weighted hypergraph partitioning problem is presented. We describe the solution of the weighted hypergraph partitioning problem based on the multi-level method. We propose the multi-level dis...
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The formal description of weighted hypergraph partitioning problem is presented. We describe the solution of the weighted hypergraph partitioning problem based on the multi-level method. We propose the multi-level discrete particle swarm optimization refinement algorithm, whose each particle's position in vertical bar V vertical bar-dimensional can be considered as the corresponded partitioning. During the refinement process of the uncoarsening phase, the algorithm projects successively each particle's corresponded partitioning back to the next-level finer hypergraph, and the degree of particle's freedom increases with the increase in solution space's dimension. The algorithm also regards the gain of vertex as particle information for the heuristic search and successfully searches the solution space based on the intelligent behavior between individuals' collaboration. Furthermore, the improved compressed storage format of weighted hypergraph is presented and the two-dimensional auxiliary array is designed for counting the vertices of each hypergraph in different partitions. The rapid method of calculating the vertex's gain and the cut's size are proposed to avoid traversing each vertex of hyperedge and reduce the algorithm's time complexity and space complexity. Experimental results show that the algorithm not only can find the better partitioning of weighted hypergraph than the move-based method but also can improve the search capability of the refinement algorithm.
Aiming at the problem of inaccurate number of bagged medicines in the packing boxes of the medicine production line, a method for counting medicine bags based on machine vision is *** method firstly performs grayscale...
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Aiming at the problem of inaccurate number of bagged medicines in the packing boxes of the medicine production line, a method for counting medicine bags based on machine vision is *** method firstly performs grayscale, image scaling, cropping,threshold segmentation and other operations on the Medicine bags images, and retains the part of the image that can effectively detect the number of pill bags, and then performs image refinement processing on it to extract the pill bag skeleton in the image. Through the feature analysis of the refined images, a multi-region target statistical counting method is proposed, and finally the number of medicine bags in the medicine box image is detected. Experimental results show that this design has high accuracy and speed for detecting the number of medicine bags in the medicine box, so this design is feasible.
To construct a high efficient text clustering algorithm, the multilevel graph model and the refinement algorithm used in the uncoarscning phase is discussed. The model is applied to text clustering. The performance of...
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To construct a high efficient text clustering algorithm, the multilevel graph model and the refinement algorithm used in the uncoarscning phase is discussed. The model is applied to text clustering. The performance of clustering algorithm has to he improved with the refinement algorithm application. The experiment result demonstrated that the multilevel graph text clustering algorithm is available.
To construct a high efficient text clustering algorithm, the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of...
详细信息
To construct a high efficient text clustering algorithm, the multilevel graph model and the refinement algorithm used in the uncoarsening phase is discussed. The model is applied to text clustering. The performance of clustering algorithm has to be improved with the refinement algorithm application. The experiment result demonstrated that the multilevel graph text clustering algorithm is available.
Longest edge (nested) algorithms for triangulation refinement in two dimensions are able to produce hierarchies of quality and nested irregular triangulations as needed both for adaptive finite element methods and for...
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Longest edge (nested) algorithms for triangulation refinement in two dimensions are able to produce hierarchies of quality and nested irregular triangulations as needed both for adaptive finite element methods and for multigrid methods for PDEs. In addition, right-triangle bintree triangulations are multiresolution algorithms used for terrain modeling and real time visualization of terrain applications. These algorithms are based on the properties of the consecutive bisection of a triangle by the median of the longest edge, and can be formulated in terms of the longest edge propagation path (Lepp) and terminal edge concepts, which implies the use of very local refinement operations over fully conforming meshes (where the intersection of pairs of neighbor triangles is either a common edge or a common vertex). In this paper we review the Lepp-bisection algorithms, their properties and applications. To the end we use recent simpler and stronger results on the complexity aspects of the bisection method and its geometrical properties. We discuss and analyze the computational costs of the algorithms. The generalization of the algorithms to 3-dimensions is also discussed. Applications of these methods are presented: for serial and parallel view dependent level of detail terrain rendering, and for the parallel refinement of tetrahedral meshes. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.
We analyse the convergence of nonlinear Riemannian analogues of linear subdivision processes operating on data in the sphere. We show how for curve subdivision rules we can derive bounds guaranteeing convergence if th...
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We analyse the convergence of nonlinear Riemannian analogues of linear subdivision processes operating on data in the sphere. We show how for curve subdivision rules we can derive bounds guaranteeing convergence if the density of input data is below that threshold. Previous results only yield thresholds that are several magnitudes smaller and are thus useless for a priori checking of convergence. It is the first time that such a result has been shown for a geometry with positive curvature and for subdivision rules not enjoying any special properties like being interpolatory or having non-negative mask.
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