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A grid-based clustering algorithm for wild bird distribution

Frontiers of Computer Science 2013年第4期7卷 475-485页

作者： Yuwei WANG Yuanchun ZHOU Ying LIU Ze LUO Danhuai GUO Jing SHAO Fei TAN Liang WU Jianhui LI Baoping YAN Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China

Advanced satellite tracking technologies provide biologists with long-term location sequence data to understand movement of wild birds then to find explicit correlation between dynamics of migratory birds and the spread of avian influenza. In this paper, we propose a hierarchical clustering algorithm based on a recursive grid partition and kernel density estimation （KDE） to hierarchically identify wild bird habitats with different densities. We hierarchically cluster the GPS data by taking into account the following observations： 1） the habitat variation on a variety of geospatial scales; 2） the spatial variation of the activity patterns of birds in different stages of the migration cycle. In addition, we measure the site fidelity of wild birds based on clustering. To assess effectiveness, we have evaluated our system using a large-scale GPS dataset collected from 59 birds over three years. As a result, our approach can identify the hierarchical habitats and distribution of wild birds more efficiently than several commonly used algorithms such as DBSCAN and DENCLUE.

关键词： hierarchical clustering bird migration kerneldensity estimation grid partition

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Multi-objective partition planning for multi-infeed HVDC system

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Global Energy Interconnection 2021年第1期4卷 81-90页

作者： Zhao Yu Shuanbao Niu Chao Huo Ning Chen Kaige Song Xiaohui Wang Yu Bai State grid Corporation of China Beijing100031P.R.China Northwest Branch State Grid Corporation of ChinaXi’an710048P.R.China National Key Laboratory of Operation and Control of Renewable Energy and Energy Storage China Electric Power Research Institute(Nanjing)Nanjing210003P.R.China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan250061P.R.China Langfang Power Supply Company State Grid Jibei Electric Power Company LimitedLangfang 065000P.R.China

The close proximity and the necessity of coordination between multiple high-voltage direct currents(HVDCs)raise the issue of grid partitioning in multi-infeed HVDC systems.A multi-objective partition strategy is proposed in this paper.Several types of relationships to be coordinated and complemented are analyzed and formulated using quantitative indices.According to the graph theory,the HVDC partition is transformed into a graph-cut problem and solved via the spectral clustering algorithm.Finally,the proposed method is validated for a practical multi-HVDC grid,confirming its feasibility and effectiveness.

关键词： Multi-infeed HVDC system grid partition Multi-objective planning Spectral clustering

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