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基于克隆選擇聚類改進的植被變化回歸趨勢分析
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國家重點基礎研究發(fā)展計劃（973計劃）資助項目(2009CB421105)和中央高校基本科研業(yè)務費專項資金資助項目(YX2011-28)


Improved Linear Trend Analysis in Vegetation Cover Change Based on Clonal Selection Clustering Algorithm
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    摘要:

    基于克隆選擇聚類算法對植被變化趨勢回歸分析中線性方程的斜率k進行聚類，并按聚類中心大小分類，解決了對斜率k的劃分問題。實驗結果表明：所提算法的DBI值0.65明顯小于與之對比3種算法的DBI值0.89、0.91和0.89。北京市城區(qū)植被變化趨勢顯著增強的結論與1998~2011年北京市城區(qū)綠化率和人均綠化面積穩(wěn)步增長的統(tǒng)計數(shù)據(jù)一致，驗證了算法的正確性，因此該方法有一定的實用性，可應用于長時序植被變化趨勢分析。

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    A clonal selection clustering algorithm was proposed to solve classification problem of the slope produced by the linear trend analysis. The experimental results showed that the DBI value of 065 was significantly less than the compared three algorithms. The result of vegetation change trend was in accord with the statistic data of greenbelt for everyone and green coverage percentage in Beijing from 1998 to 2011. So the proposed method had some application value and could widely apply in long time series of vegetation change trend analysis.

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王佃來,劉文萍.基于克隆選擇聚類改進的植被變化回歸趨勢分析[J].農業(yè)機械學報,2013,44(12):215-220. Wang Dianlai, Liu Wenping. Improved Linear Trend Analysis in Vegetation Cover Change Based on Clonal Selection Clustering Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(12):215-220.

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  • 在線發(fā)布日期: 2013-12-05
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