Forecasting of agricultural production volumes using methods of data mining

S. Kontseba, R. Lishchuk, S. Skurtol, H. Rodashchuk, I. Vasylchenko
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引用次数: 0

Abstract

In this article, the future values of indicators were forecasted for production of grains and legumes on farms in Cherkasy region based on the time series expressed in physical units. Time series analysis as one of the data mining techniques was used during the research in order to make a forecast of production using the data (based on the model of dynamic series) from past years to predict the future production volumes. This method contains the following steps: a graphical analysis (allows you to choose the model equation in the best way), separation and analysis of deterministic components of the series, smoothing and filtering of time series, study of random components, construction and testing for the adequacy of the time series model, forecasting the behavior of the time series based on the conducted research.
利用数据挖掘方法预测农业产量
本文以物理单位表示的时间序列为基础,预测了车尔喀西地区农场粮食和豆类生产的未来指标值。研究中使用了时间序列分析作为数据挖掘技术之一,利用过去年份的数据(基于动态序列模型)对产量进行预测,从而预测未来的产量。该方法包含以下步骤:图形分析(允许您以最佳方式选择模型方程),序列的确定性成分的分离和分析,时间序列的平滑和过滤,随机成分的研究,构建和测试时间序列模型的充分性,预测时间序列的行为基于所进行的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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