首页> 外文会议>Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09 >Exploratory Factor Analysis on Characteristic Indexes of Rice-irrigated Management Zones
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Exploratory Factor Analysis on Characteristic Indexes of Rice-irrigated Management Zones

机译:水稻灌溉管理区特征指标探索因素分析

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Good irrigation-management zone is the basis of agricultural water management, which can lower cost of irrigation management effectively. Irrigation management is influenced by a lot of factors (such as topography, geomorphology, climate, irrigation level and soil characteristics etc.), which makes zone partition very difficult. The paper proposes a method to conduct a proper application of Exploratory Factor Analysis (EFA) to the key index system, in which appropriate and adequate sampling data is used. The following principles or steps are adopted: Reduce the dimension of the factor space by ranking score for each of 7 indexes and then selecting factors that their accumulative contribution rate exceeds 0.8; Investigate the irrigation factors according to data acquired during the period 1952~2004 from 37 rice-irrigated experimental stations of Heilongjiang province, China; Select the key irrigated management factors depending on their factor score; and analyze the rationality of rice irrigated management zones. Three common factors are extracted that account for 81.2% of the total variation, and they are: the first common factor that includes 10¿ accumulative temperature and frostless period, the second common factor that consists of regular irrigation quota and seepage quantity, and the third principal factor for rainfall of growth period. The results from EFA provide insights into the issue of rice-irrigated management level for large-scale zones, and give a good reference to agricultural zone partition on irrigated management.
机译:良好的灌溉管理区是农业用水管理的基础,可以有效降低灌溉管理成本。灌溉管理受到许多因素的影响(例如地形,地貌,气候,灌溉水平和土壤特性等),这使得区域划分非常困难。本文提出了一种在关键指标体系中适当应用探索性因子分析(EFA)的方法,其中使用了适当和足够的采样数据。采用以下原则或步骤:通过对7个指标中的每一个进行评分,然后选择累积贡献率超过0.8的因子,来减小因子空间的维数。根据1952〜2004年从黑龙江省37个水稻灌溉试验站获得的数据调查灌溉因子;根据其因子得分选择关键灌溉管理因子;并分析了水稻灌溉管理区的合理性。提取了占总变化的81.2%的三个公因子,它们是:第一个公因子包括10°累积温度和无霜期,第二个公因子包括常规的灌溉配额和渗水量,第三个公因子生育期降雨的主要因素。全民教育的结果提供了对大面积水稻灌溉管理水平问题的见解,并为灌溉管理中的农业区划提供了很好的参考。

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