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Application of DBSCAN Algorithm in Precision Fertilization Decision of Maize

机译:DBSCAN算法在玉米精准施肥决策中的应用

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In the current era of big data, information technology is developing quite rapidly, the most important data mining technology in information technology is also widely used, and now it is applied to the field of agricultural production, what can solve many problems such as agricultural production, fertilization and so on. In this paper, data mining technology is applied to the process of corn fertilization, because in com production, effective and reasonable amount of fertilizer can make corn grow better, however, if there is no specific fertilization according to the soil properties of the corn, it will lead to the soil which needs fertility can not be with enough fertility, and the soil without fertility will be added more and more. In view of this problem, the soil planted with com was graded and treated with different levels of soil, so as to achieve the purpose of effective utilization of soil fertility. In this paper, the DBSCAN algorithm in clustering analysis is used to classify the soil, the DBSCAN algorithm to this field have not been reported so far. By applying the nutrient balance method, the amount of soil fertilizer was calculated at each level, and the fertilizer was targeted according to the amount of fertilizer. Through the pilot application in Nong'an County of Jilin province Chen hometown, compared with the traditional fertilization results, Fertilizer reduced by 25%, com production increased by about 15%, effectively reducing the input of chemical fertilizer and increasing the output of crops.
机译:在当今的大数据时代,信息技术发展迅速,信息技术中最重要的数据挖掘技术也得到了广泛的应用,如今已应用于农业生产领域,可以解决诸如农业生产等诸多问题,施肥等。本文将数据挖掘技术应用于玉米的施肥过程,因为在玉米生产中,有效合理的肥料用量可以使玉米更好地生长,但是,如果没有根据玉米的土壤特性进行特殊施肥,它将导致需要肥力的土壤不能具有足够的肥力,而没有肥力的土壤将被越来越多地添加。针对这一问题,对玉米种植的土壤进行了分级和不同程度的土壤处理,以达到有效利用土壤肥力的目的。本文采用聚类分析中的DBSCAN算法对土壤进行分类,目前尚未报道针对该领域的DBSCAN算法。通过采用养分平衡法,计算出每个水平的土壤肥料用量,并根据肥料用量确定肥料用量。通过在吉林省农安县陈家乡的试点应用,与传统的施肥效果相比,肥料减少了25%,玉米产量增加了约15%,有效地减少了化肥的投入,增加了农作物的产量。

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