利用机器学习建立预测罗马尼亚谷物净出口的最优模型

Proceedings of the International Conference Competitiveness of Agro-Food and Environmental Economy Pub Date : 2022-10-20 DOI:10.24818/cafee/2020/9/11

Robert Ştefan Sbîrcea, George Marian Calin, Iulia Bianca Bogos

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引用次数: 0

摘要

本文的目的是建立预测模型来估计罗马尼亚几种谷物的净出口。将对传统的回归模型(线性模型)和机器学习算法进行比较。此外，还将构建这些模型的集合，以最小化RMSE。其含义是复杂的，代表了数学、计量经济学和编程技能的混合。本文的结果旨在确定提高估计置信度的新方法。

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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USING MACHINE LEARNING TO BUILD AN OPTIMAL MODEL THAT FORECAST THE NET EXPORT OF CEREALS IN ROMANIA

The objectives of this article are to build forecasting models that estimate the net exports of several kinds of cereal in Romania. A comparison between the traditional model of regression (the linear model) and machine learning algorithms will be made. Moreover, there will be built an ensemble of these models in order to minimize the RMSE. The implications are complex and represent a mixture of mathematical, econometric and programming skills. The results of the article aimed to identify new methods that increase the confidence level of estimates.

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Proceedings of the International Conference Competitiveness of Agro-Food and Environmental Economy

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