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Collaborative Data Mining in Agriculture for Prediction of Soil Moisture and Temperature

机译:农业中的合作数据挖掘预测土壤水分和温度

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Climate change affects agriculture in many ways. Reducing the vulnerability of agricultural systems to climate change and enhancing their capacity to adapt would generate better results with fewer losses. Under the conditions, according to The United Nations Food and Agriculture Organization, the world has to produce 70% more food in 2050 than it produced in 2006, to feed the growing population, it is obvious that any innovative ideas that help agriculture are optimal and needed. An option for increasing efficiency of agriculture is a data mining process that can predict climate conditions and humidity of soil. Determining the optimal time for planting and harvesting could be based on predictions from a data mining process. In this scenario, the application of collaborative data mining techniques, would offer solution for the cases in which one sources do not poses useful data for mining, and the process uses date from another sources correlated.
机译:气候变化以多种方式影响农业。降低农业系统对气候变化的脆弱性,提高其适应能力将产生更好的损失结果。根据联合国粮食和农业组织的条件下,世界必须在2050年生产70%的食物,而不是2006年生产的食物,养活人口不断增长,很明显有助于农业的创新思想是最佳的需要。增加农业效率的选择是一种数据采矿过程,可以预测土壤的气候条件和湿度。确定种植和收获的最佳时间可以基于数据挖掘过程的预测。在这种情况下,协同数据挖掘技术的应用将提供解决一个来源对挖掘有用数据的情况的情况,并且该过程使用与另一个源相关的日期。

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