首页> 外文会议>IFIP international conference on computer and computing technologies in agriculture >DEFINITION OF MANAGEMENT ZONES OF SOIL NUTRIENTS BASED ON FCM ALGORITHM IN OASIS FIELD
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DEFINITION OF MANAGEMENT ZONES OF SOIL NUTRIENTS BASED ON FCM ALGORITHM IN OASIS FIELD

机译:基于FCM算法在OASIS场中的土壤营养素管理区的定义

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The objective of this research was to define management zones of oasis cotton field. The variables of organic matter, available N, available P and available K data determined in 193 topsoil (0-30cm) samples were selected as data sources. Fuzzy c-means clustering algorithm was used to delineate management zones. In order to determine the optimum fuzzy control parameters, the fuzziness performance index (FPI), c-Φ combinations and the multiple regression based on external variable were used in this study. Meanwhile, the cotton yield was chosen as the external variable. The whole field was divided in four management zones. And fuzziness exponent was 1.6. The zoning statistics showed that variation coefficient of soil nutrients decreased, while the means of the soil nutrients differed sharply between management zones. The average confusion index was 0.19 in all management zones. The overlapping of fuzzy classes at points was low and the spatial distribution of membership grades was unambiguous. The results indicated that fuzzy c-means clustering algorithm could be used to delineate management zones by selecting the appropriate external variables. The defined management zones can be used for fertilizer recommendation to manage soil nutrient more efficiently.
机译:本研究的目的是定义绿洲棉田的管理区。有机物质的变量,可用的N,可用的P和可用的K数据,在193个表身上(0-30cm)样品中确定为数据源。模糊C-means聚类算法用于描绘管理区。为了确定最佳模糊控制参数,在本研究中使用了基于外部变量的模糊性能指数(FPI),C-φ组合和多元回归。同时,选择棉花产量作为外部变量。整个领域分为四个管理区。和模糊指数为1.6。分区统计数据显示土壤营养素的变异系数下降,而土壤营养素的手段在管理区之间急剧差异。所有管理区的平均混乱指数为0.19。在点处的模糊类的重叠很低,隶属级的空间分布是明确的。结果表明,通过选择适当的外部变量,模糊C-Means聚类算法可用于描绘管理区。定义的管理区可用于施肥建议,以更有效地管理土壤营养素。

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