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There is no power source in traditional distribution network, the power flow of which is unidirectional. However, the distribution network connected renewable energy power generation is multi-directional, and the complex “multi-source” is an important feature of which. Then the protection configuration is more complex, the power quality is reduced, and the supply security is declined. Considering...
Clustering techniques have gained great popularity in neuroscience data analysis especially in analysing data from complex experiment paradigm where it is hard to apply traditional model-based method. However, when employing clustering analysis, many clustering algorithms are available nowadays and even with an individual clustering algorithm, choices like parameter settings and distance metrics are...
Wireless sensor network(WSN) are wireless self-organizing network that can monitor, perceive and gather various messages from monitoring object, then process and send them to user. For the localization algorithm of wireless sensor network exists a big positioning error in wireless communication. Wireless sensor network communication system is built up. According to the anchor nodes and unknown nodes,...
In this paper, an improved multi-objective artificial bee colony algorithm (IMOABC) is presented to synthesis the beam pattern of conformal arrays. The upper bound of conformal array efficiency (AE) is derived and the relative array efficiency is defined for the optimization object as well as the maximum side lobe level (SLL) of array beam pattern. Modified neighborhood search strategy and redefined...
In this paper, we propose a scalable clustering paradigm to address the problems of excessive computational load and limited clustering performance in large-scale data. The proposed method employs the enhanced splitting merging awareness tactics (E-SMART) algorithm. The large-scale dataset is divided into many sub-datasets sampled randomly from original data. These sub-datasets are clustered using...
Massive cloud-based data-intensive applications (e.g., iterative MapReduce-based) could involve graph data processing. How to effectively analyze and process large-scale graph data is an unsolved challenging problem. We present a parallel computation framework, named MyBSP, which is inspired by Google's Pregel system. MyBSP supports and implements the Bulk Synchronous Parallel (BSP) programming model,...
How to effectively process massive graph data is an intractable challenging issue. In this paper, two types of parallel computation approaches were compared: MapReduce and MyBSP. MyBSP is our open source implementation which adopts the Bulk Synchronous Parallel (BSP) programming model to support iterative processing. The MapReduce-based and MyBSP-based PageRank algorithms were implemented respectively...
The personalized and diverse demands of modern communication present new challenges to antenna design. While the emergence of Software-Defined Everything provides an innovative hardware design idea that hardware structure is modeled in a software way and designed with intelligence optimization algorithms. Inspired by the design idea, in this paper we propose a software-defined intelligent method for...
This paper presents the new synchronization error and cross-coupling error based on algebraic graph theory. By using these novel definitions, a task space synchronized control design procedure is proposed for multiple robotic manipulator systems (MRMS). The rigorous mathematical proof and sufficient simulation experiments are used to lay a foundation and to test the effectiveness of the new design...
Virtual machine (VM) placement is a key technologyto improve data center efficiency. Most works consider VM placement problem only with respect to physical machine(PM) or network resource optimization. However, efficient VM placement should be implemented by joint optimization of above two aspects. In this paper, a multi-objective VM placement model to minimize the number of active PMs, minimize communication...
A static dial-a-ride problem with time windows is investigated, without wait while carrying passengers and maximum ride time constraints as the service quality. A parallel insertion heuristic based on the spatial and temporal aspects is presented. The proposed algorithm firstly sorts the requests based on the earliest pickup time and decentralization index alternately and initializes the routes with...
Multi-label classification is a generalization of single-label classification, and its samples belong to multiple labels. The K-nearest neighbor algorithm can solve this problem as an optimization problem. It finds the optimum solution by caculating the distance between each sample in general. But in fact, the distance of K-nearest neighbor algorithm may be miscalculated due to the caused by the redundant...
In this paper, invasive weed optimization was used to calculate the p hases of adaptive antenna arrays for the purpose of placing null in the interfering direction and placing maximum power pattern in the desired signal direction to the far-field pattern. IWO algorithm will be stated and computed for this problem. The design results obtained with IWO have been shown to comfortably beat those obtained...
Affinity propagation clustering algorithm is with a broad value in science and engineering because of it no need to input the number of clusters in advances, robustness and good generalization. But the algorithm needs the initial similarity (the distance between any two points) as a parameter, a lot of time and storage space is required for the calculation of similarity. It's limited to apply to cluster...
This paper firstly summarizes the newest research on Available Transfer Capability (ATC) algorithm in home and abroad. By analysis of the influence of Adjusting Strategy of Generators (ASG) to power flow and transient stability, this paper derives three indexes which reflect the property of transient stability of generator based on the Equal Area Criterion (EAC). In order to improve the reliability...
In this study, a novel clustering-based selection strategy of nondominated individuals for evolutionary multi-objective optimization is proposed. The new strategy partitions the nondominated individuals in current Pareto front adaptively into desired clusters. Then one representative individual will be selected in each cluster for pruning nondominated individuals. In order to evaluate the validity...
With tremendous and ever-growing amounts of electronic documents from World Wide Web and digital libraries, it becomes more and more difficult to get information that people really want. In order to predigest search process, people use clustering method to browse through search results. However traditional Chinese information clustering techniques are inadequate since they don't generate clusters...
Because of today's explosive information from Internet, people will contact much new information at any moment. So how to analyze this non-stationary information becomes more and more important. Clustering analysis is a good information analysis method, but many clustering algorithms only fit to stationary situation. Then in this paper, a novel incremental clustering algorithm based on self-organizing-mapping-IGSOM...
In order to reduce dimension number of feature space and improve clustering precision, a novel SOM clustering algorithm based on feature selection-FSSOM is provided in this paper. This algorithm first evaluates importance and distinguishing ability of each feature, and only selects features which can efficiently improve clustering precision to construct feature space. Then, it computes kullback-leibler...
The extraction of playing shots is helpful for video analysis. In this paper, we propose an algorithm: first, the shots are segmented by detecting the shot boundaries (both abrupt cuts and gradual transitions), and wipes are discarded directly; then from the rest shots, playing shots are extracted by shot classification. Experimental results confirm the efficiency of our proposed algorithm.
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